CN113902715A - Methods, devices and media for extracting blood vessel centerlines - Google Patents
Methods, devices and media for extracting blood vessel centerlines Download PDFInfo
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Abstract
Embodiments of the present disclosure relate to methods, devices, and media for extracting vessel centerlines. According to the method, in a pre-established three-dimensional model about a blood vessel, a current section of the blood vessel is generated based on a current tracking position and a current tracking direction of the blood vessel, and the current section comprises a current central point of the blood vessel; determining a current tracking step length based on the size of the generated current tangent plane so as to determine a next tracking position of the blood vessel based on the current tracking step length and the current tracking direction; determining a next tracking direction of the blood vessel based on the current tracking direction, the current center point, the next tracking position and a predetermined angle threshold; generating a next section of the blood vessel based on the next tracking position and the next tracking direction so as to sequentially generate all sections of the blood vessel; and obtaining the central line of the blood vessel based on the central points of all the generated sections. Thus, the high-precision blood vessel center line can be accurately and efficiently extracted.
Description
Technical Field
Embodiments of the present disclosure relate generally to the field of medical image processing, and more particularly, to a method, apparatus, and medium for extracting a vessel centerline.
Background
The blood vessel centerline extraction technology is an important application branch of biomedical engineering, and is an important auxiliary means for analyzing and diagnosing cardiovascular and cerebrovascular diseases and the like. Particularly, the center line of the blood vessel has very important significance for planning the preoperative path of the blood vessel intervention, operation in the operation, monitoring the postoperative effect and the like. At present, the vessel centerline is usually extracted by a minimum path method, a centerline extraction method based on deformation or a geometric model, and a direct centerline tracking method.
The minimum path method usually implements the extraction of the center line of the blood vessel by finding a shortest path through the inside of the blood vessel between a start point and an end point in an image, the center line extracted by this method has poor smoothness in a local area, and the extracted result is not exactly located at the center of the blood vessel, and often needs a later adjustment.
The centerline extraction method based on deformation or geometric model usually requires segmenting the blood vessel object first, and then calculating the central axis by using the geometric center-of-gravity model. This method is usually time consuming and requires good image characteristics and prior knowledge as a premise, otherwise, a more accurate center line cannot be extracted.
The direct center line tracking method obtains the direction of the blood vessel at the current position by judging the local direction of the blood vessel, and then obtains a cross section of the blood vessel orthogonal to the direction of the blood vessel at the current position and a central point thereof by combining the local space information and curvature change of the blood vessel in the image; then, the current tracking point and the current tracking direction are corrected according to the central point of the cross section, and the local central point calculation process is repeated until the tail end of the blood vessel is tracked. This direct centerline tracking method is based on a local method, global information is not considered in the tracking process, so the extracted centerline is usually incomplete, and since the method is not sensitive to the overall topology of a tubular object such as a blood vessel, the centerline extraction is prone to errors in positions with large curvature variation or many branches. For example, for a special-shaped blood vessel sharp turn (e.g., sharp turn more than about 135 degrees) caused by a lesion or an external force, with such a direct centerline tracking method, such a sharp turn is often misjudged as the end of the blood vessel and stopped tracking, resulting in an incomplete extracted centerline.
Thus, there is a need for a technique for extracting a blood vessel centerline that enables accurate and highly accurate extraction of a complete and precise blood vessel centerline.
Disclosure of Invention
In view of the above problems, the present disclosure provides a method, apparatus, and medium for extracting a blood vessel centerline, which enables accurate and efficient extraction of a blood vessel centerline with high accuracy.
According to a first aspect of the present disclosure, there is provided a method for extracting a vessel centerline, comprising: generating a current section of the blood vessel based on a current tracking position and a current tracking direction of the blood vessel in a pre-established three-dimensional model of the blood vessel, wherein the current section comprises a current central point of the blood vessel; determining a current tracking step based on the size of the generated current tangent plane, so as to determine a next tracking position of the blood vessel based on the current tracking step and the current tracking direction; determining a next tracking direction of the blood vessel based on the current tracking direction, the current center point, the next tracking position, and a predetermined angle threshold; generating a next section of the blood vessel based on the next tracking position and the next tracking direction so as to sequentially generate all sections of the blood vessel; and obtaining the central line of the blood vessel based on the central points of all the generated sections.
According to a second aspect of the present disclosure, there is provided a computing device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of the first aspect of the disclosure.
In a third aspect of the present disclosure, a non-transitory computer readable storage medium is provided having stored thereon computer instructions for causing the computer to perform the method of the first aspect of the present disclosure.
In some embodiments, determining the next tracking direction of the blood vessel based on the current tracking direction, the current center point, the next tracking position, and a predetermined angle threshold comprises: generating a predicted next slice of the blood vessel based on the next tracked position and the current tracked direction, the predicted next slice comprising a predicted next center point of the blood vessel; determining whether a current included angle between a connecting line of the current central point and the predicted next central point and the current tracking direction is greater than the predetermined angle threshold; in response to determining that the current included angle is less than or equal to the predetermined angle threshold, determining that the next tracking direction is consistent with the current tracking direction; and in response to determining that the current included angle is greater than the predetermined angle threshold, determining the next tracking direction based on the current tracking direction and the current included angle such that the included angle between the next tracking direction and the current tracking direction is less than the predetermined angle threshold.
In some embodiments, deriving the centerline of the vessel based on the center points of all the generated slices of the vessel comprises: smoothing the set of the central points of all the generated tangent planes so as to obtain a smoothed central point set; interpolating between each pair of adjacent central points in the smoothed set of central points, thereby obtaining a set of interpolated central points, a spacing between adjacent central points in the set of interpolated central points being a desired spacing; and deriving the centerline of the vessel based on the set of interpolated center points.
In some embodiments, the blood vessel is a main artery blood vessel and any one of a plurality of branch blood vessels of the main artery blood vessel, and the method further comprises: generating a blocked section between the main vessel and the branch vessel.
In some embodiments, generating an interception plane between the main vessel and a branch vessel comprises: determining the normal direction of the interception section; and generating the interception plane based on any point on the intersection plane of the main vessel and each branch vessel and the normal direction, wherein the interception plane comprises an interception plane central point and an interception plane point set for limiting the interception plane.
In some embodiments, generating the current slice of the vessel based on the current tracked position and the current tracked direction of the vessel comprises: determining a first search vector and a second search vector based on the current tracking direction and the current tracking position, the first search vector and the second search vector both being perpendicular to the current tracking direction, and the first search vector and the second search vector being perpendicular to each other; determining a third search vector and a fourth search vector based on the first search vector and the second search vector, respectively, the third search vector and the fourth search vector being inverse vectors of the first search vector and the second search vector, respectively; performing breadth-first search along the first search vector, the second search vector, the third search vector, and the fourth search vector, with the current tracking position as a starting point, so as to determine a current tangent plane point set for defining the current tangent plane and a boundary point set of the current tangent plane based on the interception plane and a preset global boundary value of the three-dimensional model; and determining the current central point of the current tangent plane based on the boundary point set of the current tangent plane.
In some embodiments, the initial tracking position of the main vein is any point on the main vein, and the initial tracking direction of the main vein is a vessel extension direction of the main vein at the initial tracking position.
In some embodiments, the initial tracking position and the initial tracking direction of each branch vessel are determined based on the steps of: the initial tracking position and the initial tracking direction of each branch vessel are determined based on the following steps: acquiring the central point of the interception surface as the initial tracking position of the branch blood vessel; acquiring the nearest central point which is closest to the initial tracking position in all the central points determined for the main vessel; determining an initial tracking direction of the branch vessel based on the initial tracking position, the nearest center point, and a normal direction vector of the interception section.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
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The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. In the drawings, like or similar reference characters designate like or similar elements.
Fig. 1 shows a schematic diagram of a system 100 for implementing a method for extracting a vessel centerline according to an embodiment of the invention.
Fig. 2 shows a flow diagram of a method 200 for extracting a vessel centerline according to an embodiment of the present disclosure.
FIG. 3 shows a flow diagram of a method 300 for generating a current slice of a blood vessel in accordance with an embodiment of the present disclosure;
fig. 4 shows a flow diagram of a method 400 for determining a next tracking direction of a blood vessel according to an embodiment of the present disclosure.
FIG. 5A shows a next tracking direction principle schematic of determining a blood vessel according to an embodiment of the present disclosure;
FIG. 5B illustrates a next tracking direction principle schematic diagram for determining a blood vessel according to an embodiment of the present disclosure;
fig. 6 illustrates a block diagram of an electronic device 600 in accordance with an embodiment of the disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
The term "include" and variations thereof as used herein is meant to be inclusive in an open-ended manner, i.e., "including but not limited to". Unless specifically stated otherwise, the term "or" means "and/or". The term "based on" means "based at least in part on". The terms "one example embodiment" and "one embodiment" mean "at least one example embodiment". The term "another embodiment" means "at least one additional embodiment". The terms "first," "second," and the like may refer to different or the same object. Other explicit and implicit definitions are also possible below.
As described above, the vessel centerline is currently generally extracted using a minimum path method, a centerline extraction method based on a deformation or geometric model, and a direct centerline tracking method. However, the centerlines extracted using the minimum path method are less smooth in local areas, and the extracted results are not exactly centered in the vessel, often requiring later adjustments. The centerline extraction method based on the deformation or geometric model is usually time-consuming, and needs better image characteristics and prior knowledge as a premise, otherwise, a more accurate centerline cannot be extracted. In addition, the direct centerline tracking method is insensitive to the overall topology of the tubular object, such as a blood vessel, and thus, the centerline extraction is prone to errors at locations where curvature changes are large or where there are many branches.
To address at least in part one or more of the above issues and other potential issues, an example embodiment of the present disclosure proposes a method for extracting a vessel centerline, comprising: generating a current section of the blood vessel based on a current tracking position and a current tracking direction of the blood vessel in a pre-established three-dimensional model of the blood vessel, wherein the current section comprises a current central point of the blood vessel; determining a current tracking step based on the size of the generated current tangent plane, so as to determine a next tracking position of the blood vessel based on the current tracking step and the current tracking direction; determining a next tracking direction of the blood vessel based on the current tracking direction, the current center point, the next tracking position, and a predetermined angle threshold; generating a next section of the blood vessel based on the next tracking position and the next tracking direction so as to sequentially generate all sections of the blood vessel; and obtaining the central line of the blood vessel based on the central points of all the generated sections. In this way, a high accuracy of vessel centerlines is enabled to be accurately and efficiently extracted, thereby making it possible to provide, for example, medical workers (such as doctors) with more accurate reference data for, for example, preoperative planning, thereby facilitating a reduction in operation time and a reduction in operation risk.
Fig. 1 shows a schematic diagram of a system 100 for implementing a method for extracting a vessel centerline according to an embodiment of the invention. As shown in fig. 1, system 100 includes a computing device 110, a network 120, and a server 130. Computing device 110 and server 130 may interact with data via network 120 (e.g., the internet). In the present disclosure, server 130 may be used as a server to build a three-dimensional model of a blood vessel. Computing device 110 may communicate with server 130 via network 120 to obtain a three-dimensional model of a blood vessel built by the server. The computing device 110 may include at least one processor 112 and at least one memory 114 coupled to the at least one processor 112, the memory 114 having stored therein instructions 116 executable by the at least one processor 112, the instructions 116 when executed by the at least one processor 112 performing the method 200 as described below. Note that herein, computing device 110 may be part of server 130 or may be separate from server 130. The specific structure of computing device 110 or server 130 may be described, for example, in connection with FIG. 6 below.
Fig. 2 shows a flow diagram of a method 200 for extracting a vessel centerline according to an embodiment of the present disclosure. The method 200 may be performed by the computing device 110 as shown in FIG. 1, or may be performed at the electronic device 600 shown in FIG. 6. It should be understood that method 200 may also include additional blocks not shown and/or may omit blocks shown, as the scope of the present disclosure is not limited in this respect.
In step 202, the computing device 110 generates a current cut plane of the blood vessel based on the current tracked position and the current tracked direction of the blood vessel in the pre-established three-dimensional model of the blood vessel, the current cut plane including a current center point of the blood vessel.
The pre-established three-dimensional model of the blood vessel may be a three-dimensional model automatically generated based on a medical image of the blood vessel using an Artificial Intelligence (AI) model. A three-dimensional model of the vessel can be realized by means of image segmentation. Image segmentation refers to dividing an image into several regions and extracting an anatomical structure or a region of interest (in this disclosure, a blood vessel region) in the image. In some embodiments, image segmentation based on a depth learning model may be utilized to extract vessel regions from each of a plurality of axial tomographic images of a vessel, and then generate a three-dimensional mesh model of the vessel based on these vessel regions. The deep learning model may be, for example, a convolutional neural network model, a three-dimensional Unet network model, or the like. In the present disclosure, the three-dimensional model of the blood vessel may include a three-dimensional model of the main vessel blood vessel and a three-dimensional model of each branch blood vessel.
In the present disclosure, generating a current slice of the blood vessel based on the current tracked position and the current tracking direction of the blood vessel refers to generating a current slice of the blood vessel passing through the current tracked position and orthogonal to the current tracking direction.
In some embodiments, the current slice is generated by acquiring a plurality of points located on the slice based on the current tracking position and the current tracking direction. In these embodiments, in addition to acquiring the current center point of the blood vessel, a current slice point set for defining a current slice and a current slice boundary point set for defining a boundary of the current slice are acquired. For example, in the case that the current tangent plane is a circular section, the current tangent plane point set refers to a set of points extending over the circular section, for example, a set of coordinates of a plurality of pixel points extending over the circular section), and the boundary of the current tangent plane may not be included in the set. The current section boundary point set refers to a set of a plurality of points extending over the circumference of the current section, for example, a set of coordinates of a plurality of pixel points extending over the circumference of the current section). The method 300 for generating a current section of a blood vessel is described in further detail below in conjunction with FIG. 3.
In the present disclosure, the blood vessel referred to in step 202 may be a main artery blood vessel or any one of a plurality of branch blood vessels of the main artery blood vessel. Also, in the present disclosure, the method 200 may further include generating an interception surface between the main vein vessel and the branch vessel, i.e., a communication surface between the main vein vessel and the branch vessel. In the present disclosure, the method may further include generating an interception surface between the primary branch vessel and each secondary branch vessel of the primary branch vessel, i.e., a communication surface between the primary branch vessel and each secondary branch vessel. As will be described further below, each interception plane may be generated based on a method similar to method 300 shown in FIG. 3. It should be understood that the primary branch vessel refers to a branch vessel of the main artery vessel, and the secondary branch vessel refers to a branch vessel of the primary branch vessel. Since the branch vessels (i.e., the three-dimensional models of the branch vessels) affect the correct direction of the central line of the main vessel, and the secondary branch vessels also affect the correct direction of the central line of the primary branch vessel, the information of the relevant interception planes needs to be considered when extracting the central line of the main vessel and the central lines of the branch vessels, so as to avoid the influence of the branch vessels. For example, if the interception plane between the branch vessel and the main vessel of the main vessel is not determined, the boundary of the main vessel may not be determined, and the center line of the main vessel may not be correctly determined. In addition, the interception surface can intercept part of lesion areas or abnormal areas caused by thrombus or calcification, so that the negative influence of the heterogeneity on the calculation of the center line of the blood vessel can be greatly reduced by generating the interception surface, and the accuracy of the starting tracking position and the starting tracking direction of the center of each branch blood vessel can be ensured.
In the present disclosure, for a main artery blood vessel, its initial tracking position may be any point on the main artery blood vessel, and its initial tracking direction may be a blood vessel extending direction of the main artery blood vessel at the initial tracking position. For example, if the main vein is extended up and down at the initial tracking position, the initial tracking direction of the main vein may be an upward direction along the main vein or a downward direction along the main vein. Starting from this initial tracking position and initial tracking direction of the main vein, the method 200 is performed, which effectively extracts the centerline of the main vein.
For each branch vessel, its initial tracking position and initial tracking direction may be determined based on: first, the intercept plane center point of the intercept plane between the branch vessel and the main vessel is acquired as the initial tracking position (for example, denoted by P) of the branch vessel. Then, the closest central point (for example, with C) closest to the initial tracking position of the branch vessel among all the central points determined for the main vessel is acquiredM1Representation). Finally, an initial tracking direction of the branch vessel is determined based on the initial tracking position, the nearest center point and a normal direction vector of the interception plane. In some implementations, the normal direction vector of the interception surface may be determined based on any three points in the set of interception surface points used to define the interception surface, since the plane in which the interception surface lies may be determined from the three points, and then the normal direction vector of the interception surface (e.g., represented by Norm) may be determined by determining the normal direction vector of the plane. For example, P will be the starting point and CM1The direction vector as an end point is denoted PCM1If PCM1And if the included angle between the normal direction and the Norm is larger than 90 degrees, determining that the normal direction Norm is the initial tracking direction of the interception surface, otherwise, determining that the reverse direction of the normal direction Norm is the initial tracking direction of the interception surface. Starting from the initial tracking position and initial tracking direction of each branch vessel, the method 200 is performed to effectively extract the centerline of the branch vessel.
In step 204, a current tracking step is determined based on the size of the generated current slice, so as to determine a next tracking position of the blood vessel based on the current tracking step and the current tracking direction.
In the present disclosure, the size of the generated current slice refers to the size of the area of the current slice. As previously described, in some embodiments, the current facet may be generated by obtaining points located on the facet, i.e., by obtaining a current set of facet points defining the current facet and a current set of facet boundary points defining the boundary of the current facet, so the size of the area of the current facet may be indicated by the number of points contained in the current set of facet points.
In the present disclosure, the current tracking step size is proportional to the size of the current tangent plane, for example, the larger the size of the current tangent plane is, the larger the current tracking step size is, and otherwise, the smaller the current tracking step size is. Three-dimensional models of blood vessels are very complex and therefore cannot be applied to all vascular environments if a single step size is used. If the tracking step is too small, excessive computing resources and time are required to obtain the centerline of the whole blood vessel, and if the tracking step is too large, the end of the blood vessel may be misjudged at the turn of the blood vessel, so that the extraction of the centerline of the blood vessel is stopped, and the centerline of the extracted blood vessel is incomplete. In the present disclosure, the current tracking step is determined based on the size of the current slice, so that in the process of extracting the centerline of the blood vessel, the tracking step is not fixed but varies according to the size of the current slice. That is, in the process of gradually generating the section of the blood vessel from the initial tracking position of the blood vessel, the tracking step length can be modified in real time based on the data of the current section, and the next tracking position is determined accordingly, so that the extraction efficiency of the center line of the blood vessel can be greatly improved.
At step 206, a next tracking direction of the blood vessel is determined based on the current tracking direction, the current center point, the next tracking position, and a predetermined angle threshold.
In the present disclosure, determining the next tracking direction of the blood vessel based on the current tracking direction, the current center point, the next tracking position, and the predetermined angle threshold may help to avoid misjudging a location where a turn of the blood vessel is obvious (e.g., a sharp turn of the blood vessel having a shape such as a sharp turn of more than 135 degrees due to a lesion or an external force) or later as the tip of the blood vessel, thereby helping to extract the center line of the blood vessel more accurately.
Step 206 is described in further detail below in conjunction with fig. 4.
In step 208, a next slice of the blood vessel is generated based on the next tracked position and the next tracked direction, such that all slices of the blood vessel are generated in sequence.
In particular, after the next tracking position and the next tracking direction have been determined, all other sections of the vessel may be generated in turn in the manner of step 202-. For example only, if the initial tracking position is obtained at the beginning of a blood vessel, it may be determined that all slices of the blood vessel have been generated when the end of the blood vessel is reached.
At step 210, based on the center points of all the slices of the generated vessel, the centerline of the vessel is obtained.
In some embodiments, step 210 may include smoothing the generated set of center points of all the facets (i.e., the coordinates of the center points of all the facets) to obtain a smoothed set of center points. The smoothing process can contribute to obtaining a more accurate blood vessel center line.
The set of center points of all the generated facets may be smoothed based on, for example, a moving average (moving average) algorithm. For example, an average value (n is an integer of 2 or more) is obtained for every n center points of the center points of all the generated tangent planes, and a set of the obtained average values is used as a set of center points subjected to smoothing processing. For example, if n is 2, then one averages over the first and second center points, then one averages over the second and third center points, then one averages over the third and fourth center points, and so on, up to the last center point, and then takes the set of all the resulting averages as the smoothed set of center points, by way of example only.
Step 210 may further include interpolating between each pair of adjacent center points in the smoothed set of center points, thereby obtaining a set of interpolated center points having a desired spacing between adjacent center points in the set of interpolated center points.
In particular, the set of smoothed center points may be based (e.g., each midpoint in the set may be respectively denoted as c)1、c2、c3、c4… …) are used to construct a vector (e.g., respectively represented as vector c)1c2、c2c3、c3c4… …) and then normalizing the vectors to obtain corresponding unit vectors (e.g., represented as unit vector n)1n2、n2n3、n3n4… …). If the desired spacing is represented as r, the location of each new center point to be inserted may be determined based on the following formula: c. Ca+r*nanb. For example, if adjacent center point caAnd cbThe distance between the two adjacent center points is 1mm, and the expected distance r is 0.2mm, the two adjacent center points are required to be arranged at the adjacent center points caAnd cbFour new center points are inserted between the two points, and the positions of the four new center points are respectively: c. Ca+0.2*nanb、ca+0.2*nanb+0.2*nanb、ca+0.2*nanb+0.2*nanb+0.2*nanb、ca+0.2*nanb+0.2*nanb+0.2*nanb+0.2*nanb。
By the above method, an interpolated set of center points with a spacing r between adjacent center points is finally obtained, which may be denoted as C, for exampleM。
Step 210 may also include deriving the centerline of the vessel based on the set of interpolated center points.
For example, by connecting the set of interpolated center points CMAll the central points in the process can finally obtain the high-precision blood vessel central line.
Fig. 3 shows a flow diagram of a method 300 for generating a current slice of a blood vessel according to an embodiment of the present disclosure. The method 300 may be performed by the computing device 110 as shown in FIG. 1, or may be performed at the electronic device 600 shown in FIG. 6. It should be understood that method 300 may also include additional blocks not shown and/or may omit blocks shown, as the scope of the disclosure is not limited in this respect.
In step 302, based on the current tracking direction and the current tracking position, a first search vector and a second search vector are determined, the first search vector and the second search vector are both perpendicular to the current tracking direction, and the first search vector and the second search vector are perpendicular to each other. In this disclosure, the first search vector and the second search vector are unit vectors. In addition, in the present disclosure, since the first search vector and the second search vector are determined based on the current tracking position and both the first search vector and the second search vector are perpendicular to the current tracking direction, both the first search vector and the second search vector should fall on the current tangent plane. For example, the starting points of the first search vector and the second search vector may be the current tracking position.
In step 304, a third search vector and a fourth search vector are determined based on the first search vector and the second search vector, respectively, the third search vector and the fourth search vector being inverted vectors of the first search vector and the second search vector, respectively. In this disclosure, since the third search vector and the fourth search vector should also fall on the current tangent plane.
In step 306, a breadth-first search is performed along the first search vector, the second search vector, the third search vector, and the fourth search vector, starting from the current tracking position, so as to determine a current tangent plane set defining the current tangent plane and a boundary point set of the current tangent plane based on the interception plane and a preset global boundary value of the three-dimensional model (i.e., the aforementioned three-dimensional model of the blood vessel).
The breadth-first search process includes performing an unordered search in four directions of the first search vector, the second search vector, the third search vector, and the fourth search vector, respectively, by taking the current tracking position as a starting point, so as to search a set of all points defining the current tangent plane (also referred to as a current tangent plane point set of the current tangent plane) and a set of all points defining a boundary of the current tangent plane (also referred to as a boundary point set of the current tangent plane). Specifically, the process may include, taking the current tracking position as a starting point, respectively advancing a search step along four directions of a first search vector, a second search vector, a third search vector, and a fourth search vector to collect coordinates of four points fed back by the search, then respectively advancing a search step along four directions of the first search vector, the second search vector, the third search vector, and the fourth search vector with each of the four points as a starting point, thereby collecting four points for each search, and so on until a search range exceeds a boundary position of the current tangent plane. The threshold value for the global boundary position of the three-dimensional model of the blood vessel may be preset to 0, for example. Therefore, in the above unordered search process, if the feedback value of the search is 0 or the coordinate point on the interception surface, it indicates that the search distance of the current search step exceeds the boundary range of the current tangent plane, and therefore, the previous search (i.e., the search of the previous starting point) needs to be performed, and this is repeated until all the feedback values along each of the four directions are 0 or the coordinate point on the interception surface, and the search process is ended. Through the above search process, all points related to the current tangent plane may be collected, including the current tangent plane point set for defining the current tangent plane and the boundary point set of the current tangent plane.
In the present disclosure, the search step size may be a pixel pitch, for example, a pixel pitch on each image used to construct the three-dimensional model.
At step 308, a current center point of the current tangent plane is determined based on the set of boundary points of the current tangent plane.
In the present disclosure, based on the collected coordinate values to each boundary, a center point of the current tangent plane, that is, a coordinate value of the center point of the current tangent plane, may be obtained. For example, the coordinate value of the center point of the current tangent plane can be obtained by calculating the average value of the searched boundary coordinate values.
By adopting the means, the current tangent plane can be accurately and quickly generated.
As previously mentioned, the method 200 may also include generating an interception surface between the main vessel and each branch vessel. In the present disclosure, generating an interception plane between the main vessel and each branch vessel may include: the normal direction of the interception surface is determined, and then a interception plane is generated based on any point on the intersection surface of the main vessel and each branch vessel and the normal direction, wherein the interception surface comprises an interception plane central point and an interception plane point set used for limiting the interception plane.
In some embodiments, the normal direction of the interception plane may be determined by: first, any three points on the intersection surface of the main vein blood vessel and the corresponding branch blood vessel are obtained, and then the normal direction of the plane defined by the three points is determined, and the normal direction of the plane defined by the three points corresponds to the normal direction of the interception surface. After determining the normal direction of the intercepting surface, a block plane may be generated based on any one of the three points and the normal direction.
In other embodiments, the normal direction of the dam section may be determined by: acquiring any two points on the intersection surface of the main vessel and the corresponding branch vessel; then, starting from these two points, respectively, a direction vector (defined as the interception direction) on the interception face is obtained, which may be denoted hereinafter as V1 and V2, for example. In the present disclosure, V1 and V2 may be directions in which the eyes of the observer look toward the dam section from the aforementioned two points, respectively, for example. Finally, based on the two direction vectors V1 and V2, a direction vector perpendicular to both V1 and V2, i.e., a normal direction perpendicular to the plane (i.e., the intercepting surface) where V1 and V2 are located, is obtained according to a vector cross-product operation. After determining the normal direction of the intercepting surface, a blocking plane may be generated based on any one of the two points and the normal direction.
In the present disclosure, generating the interception plane based on any point on the intersection plane of the main vessel and each branch vessel (e.g., any one of the three points mentioned above or any one of the two points mentioned above, but may also be other points on the intersection plane) and the normal direction is similar to the method 300 for generating the current tangent plane of the vessel described above, and it is only necessary to replace the current tracking position in the method 300 with the position of any point (e.g., the coordinates of any one of the three points mentioned above or the coordinates of any one of the two points mentioned above), replace the current tracking direction with the normal direction, and replace the current tangent plane with the interception plane, so further description will not be given herein.
Fig. 4 shows a flow diagram of a method 400 for determining a next tracking direction of a blood vessel according to an embodiment of the present disclosure. The method 400 may be performed by the computing device 110 as shown in FIG. 1, or may be performed at the electronic device 600 shown in FIG. 6. It should be understood that method 400 may also include additional blocks not shown and/or may omit blocks shown, as the scope of the disclosure is not limited in this respect.
At step 402, a predicted next slice of the blood vessel is generated based on the next tracked position and the current tracked direction, the predicted next slice including a predicted next center point of the blood vessel.
In the present disclosure, generating the predicted next slice of the blood vessel based on the next tracking position and the current tracking direction refers to generating a current slice of the blood vessel passing through the next tracking position and orthogonal to the current tracking direction. Step 402 is substantially the same as step 202 described above, except that in step 402, the predicted next slice is generated and the predicted next slice is generated based on the next tracking position and the current tracking direction, rather than the current tracking position and the current tracking direction, and therefore, for brevity, further description thereof is omitted here.
At step 404, it is determined whether a current angle between a line connecting the current center point and the expected next center point and the current tracking direction (i.e., the normal direction of the current tangent plane) is greater than a predetermined angle threshold.
The current included angle may be determined, for example, based on the following equation (1):
where θ represents the current angle, (x1, x2, x3) is a vector representing a line connecting the current center point and the predicted next center point, and (y1, y2, y3) is a vector representing the current tracking direction.
In the present disclosure, a predetermined angle threshold is pre-specified, and the comparison between the current included angle between the connection line between the current center point and the predicted next center point and the current tracking direction and the predetermined angle threshold can be used to determine whether the predicted next tangent plane generated in step 403 is an invalid tangent plane, and if the predicted next tangent plane is an invalid tangent plane, the information related to the tangent plane is not recorded, but a new tracking direction is searched again. Because if such a predicted next section is still considered to be a valid section, as shown in fig. 5A, it may result in misjudgment of the end of the blood vessel, resulting in an incomplete centerline of the finally extracted blood vessel.
At step 406, in response to determining that the current angle is less than or equal to the predetermined angle threshold, the next tracking direction is determined to be consistent with the current tracking direction.
In the present disclosure, if it is determined that the current included angle is less than or equal to the predetermined angle threshold, it may be determined that the predicted next slice is a valid slice, and thus there is no need to re-explore a new tracking direction, because the current tracking direction is sufficient to find a satisfactory next slice, and thus the next tracking direction may be consistent with the current tracking direction.
At step 408, in response to determining that the current angle is greater than the predetermined angle threshold, a next tracking direction is determined based on the current tracking direction and the current angle such that the angle between the next tracking direction and the current tracking direction is less than the predetermined angle threshold.
For example, as shown in fig. 5A, the current angle between the connection line between the current center point and the predicted next center point and the current tracking direction is greater than the predetermined angle threshold, so the predicted next slice in fig. 5A is an invalid slice, and a new tracking direction, i.e., the next tracking direction, needs to be re-explored to generate a suitable next slice.
In some embodiments, it may be determined whether one-half of the current angle obtained in step 404 is greater than the predetermined angle threshold, and if one-half of the current angle is less than or equal to the predetermined angle threshold, a direction having one-half of the current angle with the current tracking direction is selected as the next tracking direction. If one-half of the current angle is still greater than the predetermined angle threshold, then a determination is made as to whether one-quarter of the current angle obtained at step 404 is greater than the predetermined angle threshold, and the above process is repeated until a suitable next tracking direction is found. For example, as shown in fig. 5B, through the above procedure, a suitable next tracking direction is found. Based on the appropriate next tracking direction and the next tracking position, an effective next slice, such as the next slice shown in fig. 5B, may be generated.
By adopting the above means, the present disclosure can effectively avoid misjudging a position where a turn of a blood vessel is obvious or later as the tip of the blood vessel, thereby contributing to more accurately extracting the center line of the blood vessel.
FIG. 6 illustrates a schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure. For example, the computing device 110 as shown in fig. 1 may be implemented by the electronic device 600. As shown, electronic device 600 includes a Central Processing Unit (CPU)601 that can perform various appropriate actions and processes in accordance with computer program instructions stored in a Read Only Memory (ROM)602 or loaded from a storage unit 608 into a Random Access Memory (RAM) 603. In the random access memory 603, various programs and data required for the operation of the electronic apparatus 600 can also be stored. The central processing unit 601, the read only memory 602, and the random access memory 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
A number of components in the electronic device 600 are connected to the input/output interface 605, including: an input unit 606 such as a keyboard, a mouse, a microphone, and the like; an output unit 607 such as various types of displays, speakers, and the like; a storage unit 608, such as a magnetic disk, optical disk, or the like; and a communication unit 609 such as a network card, modem, wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The various processes and processes described above, such as methods 200, 300, and 400, may be performed by central processing unit 601. For example, in some embodiments, methods 200, 300, and 400 may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 600 via the read only memory 602 and/or the communication unit 609. When the computer program is loaded into the random access memory 603 and executed by the central processing unit 601, one or more of the actions of the methods 200, 300 and 400 described above may be performed.
The present disclosure relates to methods, apparatuses, systems, electronic devices, computer-readable storage media and/or computer program products. The computer program product may include computer-readable program instructions for performing various aspects of the present disclosure.
The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge computing devices. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.
The computer program instructions for carrying out operations of the present disclosure may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, the electronic circuitry that can execute the computer-readable program instructions implements aspects of the present disclosure by utilizing the state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).
Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer-readable program instructions may be provided to a processing unit of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processing unit of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (10)
1. A method for extracting a vessel centerline, comprising:
generating a current section of the blood vessel based on a current tracking position and a current tracking direction of the blood vessel in a pre-established three-dimensional model about the blood vessel, wherein the current section comprises a current central point of the blood vessel;
determining a current tracking step based on the size of the generated current tangent plane, so as to determine a next tracking position of the blood vessel based on the current tracking step and the current tracking direction;
determining a next tracking direction of the blood vessel based on the current tracking direction, the current center point, the next tracking position, and a predetermined angle threshold;
generating a next section of the blood vessel based on the next tracking position and the next tracking direction so as to sequentially generate all sections of the blood vessel; and
obtaining a center line of the blood vessel based on the generated center points of all the sections of the blood vessel.
2. The method of claim 1, wherein determining a next tracking direction of the blood vessel based on the current tracking direction, the current center point, the next tracking location, and a predetermined angular threshold comprises:
generating a predicted next slice of the blood vessel based on the next tracked position and the current tracked direction, the predicted next slice comprising a predicted next center point of the blood vessel;
determining whether a current included angle between a connecting line of the current central point and the predicted next central point and the current tracking direction is greater than the predetermined angle threshold;
in response to determining that the current included angle is less than or equal to the predetermined angle threshold, determining that the next tracking direction is consistent with the current tracking direction; and
in response to determining that the current included angle is greater than the predetermined angle threshold, determining the next tracking direction based on the current tracking direction and the current included angle such that the included angle between the next tracking direction and the current tracking direction is less than the predetermined angle threshold.
3. The method of claim 1, wherein deriving a centerline of the vessel based on center points of all generated slices of the vessel comprises:
smoothing the set of the central points of all the generated tangent planes so as to obtain a smoothed central point set;
interpolating between each pair of adjacent central points in the smoothed set of central points, thereby obtaining a set of interpolated central points, a spacing between adjacent central points in the set of interpolated central points being a desired spacing; and
deriving the centerline of the vessel based on the set of interpolated center points.
4. The method of any one of claims 1 to 3, wherein the blood vessel is a main artery blood vessel or any one of a plurality of branch blood vessels of the main artery blood vessel, and the method further comprises:
generating a blocked section between the main vessel and the branch vessel.
5. The method of claim 4, wherein generating an interception plane between the main vessel and a branch vessel comprises:
determining the normal direction of the interception section; and
and generating the interception plane based on any point on the intersection plane of the main vessel and each branch vessel and the normal direction, wherein the interception plane comprises an interception plane central point and an interception plane point set for limiting the interception plane.
6. The method of claim 5, wherein generating a current slice of a vessel based on a current tracked position and a current tracked direction of the vessel comprises:
determining a first search vector and a second search vector based on the current tracking direction and the current tracking position, the first search vector and the second search vector both being perpendicular to the current tracking direction, and the first search vector and the second search vector being perpendicular to each other;
determining a third search vector and a fourth search vector based on the first search vector and the second search vector, respectively, the third search vector and the fourth search vector being inverse vectors of the first search vector and the second search vector, respectively;
performing breadth-first search along the first search vector, the second search vector, the third search vector, and the fourth search vector, with the current tracking position as a starting point, so as to determine a current tangent plane point set for defining the current tangent plane and a boundary point set of the current tangent plane based on the interception plane and a preset global boundary value of the three-dimensional model; and
and determining the current central point of the current tangent plane based on the boundary point set of the current tangent plane.
7. The method of claim 1, wherein the initial tracked position of the main vein is any point on the main vein, and the initial tracked direction of the main vein is a vessel extension direction of the main vein at the initial tracked position.
8. The method of claim 5, wherein the initial tracking position and initial tracking direction of each branch vessel are determined based on:
acquiring the central point of the interception surface as the initial tracking position of the branch blood vessel;
acquiring the nearest central point which is closest to the initial tracking position in all the central points determined for the main vessel; and
determining an initial tracking direction of the branch vessel based on the initial tracking position, the nearest center point, and a normal direction vector of the interception section.
9. A computing device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor;
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-8.
10. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-8.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114723684A (en) * | 2022-03-22 | 2022-07-08 | 推想医疗科技股份有限公司 | Model training method and device, and vascular structure generation method and device |
| CN117115150A (en) * | 2023-10-20 | 2023-11-24 | 柏意慧心(杭州)网络科技有限公司 | Method, computing device and medium for determining branch vessels |
| CN119205724A (en) * | 2024-11-14 | 2024-12-27 | 柏意慧心(杭州)网络科技有限公司 | A method, device, equipment and medium for evaluating blood vessel wall status |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120201442A1 (en) * | 2011-02-09 | 2012-08-09 | Siemens Aktiengesellschaft | Method and computer system for automatically generating a statistical model |
| CN106875375A (en) * | 2016-12-28 | 2017-06-20 | 浙江工业大学 | Three-dimensional blood vessel axis detection method based on tubulose feature enhancing filtering and ridge line tracking |
| WO2019195926A1 (en) * | 2018-04-09 | 2019-10-17 | 7D Surgical Inc. | Systems and methods for performing intraoperative guidance |
| CN110910370A (en) * | 2019-11-21 | 2020-03-24 | 北京理工大学 | CTA image coronary stenosis detection method and device |
-
2021
- 2021-10-12 CN CN202111188627.0A patent/CN113902715B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120201442A1 (en) * | 2011-02-09 | 2012-08-09 | Siemens Aktiengesellschaft | Method and computer system for automatically generating a statistical model |
| CN106875375A (en) * | 2016-12-28 | 2017-06-20 | 浙江工业大学 | Three-dimensional blood vessel axis detection method based on tubulose feature enhancing filtering and ridge line tracking |
| WO2019195926A1 (en) * | 2018-04-09 | 2019-10-17 | 7D Surgical Inc. | Systems and methods for performing intraoperative guidance |
| CN110910370A (en) * | 2019-11-21 | 2020-03-24 | 北京理工大学 | CTA image coronary stenosis detection method and device |
Non-Patent Citations (2)
| Title |
|---|
| 杨绍洲等: "一种数字减影图像中血管的自适应跟踪算法", 《中国医学物理学杂志》, 31 December 1997 (1997-12-31), pages 1 - 3 * |
| 王胜军等: "一种基于管状特征的冠脉中心线自动提取算法", 《东 北 大 学 学 报 ( 自 然 科 学 版 )》, 31 January 2011 (2011-01-31), pages 1 - 5 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114723684A (en) * | 2022-03-22 | 2022-07-08 | 推想医疗科技股份有限公司 | Model training method and device, and vascular structure generation method and device |
| CN117115150A (en) * | 2023-10-20 | 2023-11-24 | 柏意慧心(杭州)网络科技有限公司 | Method, computing device and medium for determining branch vessels |
| CN117115150B (en) * | 2023-10-20 | 2024-01-26 | 柏意慧心(杭州)网络科技有限公司 | Method, computing device and medium for determining branch vessels |
| CN119205724A (en) * | 2024-11-14 | 2024-12-27 | 柏意慧心(杭州)网络科技有限公司 | A method, device, equipment and medium for evaluating blood vessel wall status |
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