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CN111067670A - Acetabular bone defect assessment method and device and electronic equipment - Google Patents

Acetabular bone defect assessment method and device and electronic equipment Download PDF

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CN111067670A
CN111067670A CN201911349750.9A CN201911349750A CN111067670A CN 111067670 A CN111067670 A CN 111067670A CN 201911349750 A CN201911349750 A CN 201911349750A CN 111067670 A CN111067670 A CN 111067670A
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CN111067670B (en
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庞博
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Beijing Yidian Lingdong Technology Co ltd
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Beijing AK Medical Co Ltd
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
    • A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
    • A61F2/02—Prostheses implantable into the body
    • A61F2/30—Joints
    • A61F2/32—Joints for the hip
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
    • A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
    • A61F2/02—Prostheses implantable into the body
    • A61F2/30—Joints
    • A61F2/3094—Designing or manufacturing processes
    • A61F2/30942—Designing or manufacturing processes for designing or making customized prostheses, e.g. using templates, CT or NMR scans, finite-element analysis or CAD-CAM techniques
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
    • A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
    • A61F2/02—Prostheses implantable into the body
    • A61F2/30—Joints
    • A61F2/32—Joints for the hip
    • A61F2/34—Acetabular cups
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
    • A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
    • A61F2/02—Prostheses implantable into the body
    • A61F2/30—Joints
    • A61F2/3094—Designing or manufacturing processes
    • A61F2/30942—Designing or manufacturing processes for designing or making customized prostheses, e.g. using templates, CT or NMR scans, finite-element analysis or CAD-CAM techniques
    • A61F2002/30943—Designing or manufacturing processes for designing or making customized prostheses, e.g. using templates, CT or NMR scans, finite-element analysis or CAD-CAM techniques using mathematical models

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  • Orthopedic Medicine & Surgery (AREA)
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  • Manufacturing & Machinery (AREA)
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  • Prostheses (AREA)

Abstract

The invention discloses an acetabular bone defect assessment method and device and electronic equipment. Wherein, the method comprises the following steps: determining a plurality of assessment factors for assessing an acetabular bone; determining the characteristic weight and the initial defect degree of each evaluation factor based on the acetabulum bone image of the target user; determining the factor grade of each evaluation factor based on the feature weight and the initial defect degree; and dividing the regions based on the factor grades and the grades of all the evaluation factors to evaluate the defect degree of the acetabular bones of the target users. The invention solves the technical problems that most of acetabulum bone defect degree is manually evaluated by experience in related technologies, the evaluation result difference is large, and the accuracy is reduced.

Description

Acetabular bone defect assessment method and device and electronic equipment
Technical Field
The invention relates to the technical field of data processing, in particular to an acetabular bone defect assessment method and device and electronic equipment.
Background
In the related art, many patients receive hip arthroplasty, but as the age of the patient receiving total hip arthroplasty is continuously increased and the activity is increased, the number of hip revision operations is continuously increased, in the case of hip revision after initial hip arthroplasty failure and in the case of increasingly increased hip revision patients, the acetabular bone defect treatment principle is to restore and store the bone mass of the patient as much as possible, obtain sufficient prosthesis coverage to ensure good initial stability of the prosthesis, and generate fusion redistribution between the implanted bone and the implant and host bone, at this time, the acetabular bone defect degree needs to be determined, but the current acetabular bone defect degree determination method is mostly to determine the acetabular bone defect degree of the patient by an image analysis method (e.g. CT radiography), which is to allow a doctor to check radiographic images and analyze the bone defect degree by experience, the analysis accuracy can be different greatly according to the experiences of different people, and the obtained defect degree evaluation result cannot provide a reasonable and accurate bone defect degree evaluation result.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the invention provides an acetabular bone defect assessment method, an acetabular bone defect assessment device and electronic equipment, and aims to at least solve the technical problems that most of people use experience to assess acetabular bone defect degree in related technologies, assessment results are large in difference, and accuracy is reduced.
According to an aspect of an embodiment of the present invention, there is provided an acetabular bone defect assessment method applied to a bone defect degree assessment apparatus for a hip joint, the assessment method including: determining a plurality of assessment factors for assessing an acetabular bone; determining the characteristic weight and the initial defect degree of each evaluation factor based on the acetabulum bone image of the target user; determining the factor grade of each evaluation factor based on the feature weight and the initial defect degree; and dividing the regions based on the factor grades and the grades of all the evaluation factors to evaluate the defect degree of the acetabular bones of the target users.
Optionally, the step of determining the feature weight and the initial defect degree of each evaluation factor includes: analyzing the acetabular bone image to obtain characteristic information of the acetabular bone side; determining the information entropy of each evaluation factor by adopting an entropy weight calculation method, and calculating the characteristic weight of each evaluation factor based on the information entropy; determining a factor grade, a difference degree component and a difference degree component coefficient of each evaluation factor based on the characteristic information; combining each evaluation factor and factor grade into a set-pair relation by adopting a set-pair theoretical analysis method; and quantizing the initial defect degree of the evaluation factor based on the set pair relationship, the difference degree component and the difference degree component coefficient.
Optionally, the step of determining a factor grade of each evaluation factor based on the feature weight and the initial defect degree includes: determining the grade weight number and the discrete grade of each evaluation factor based on the characteristic weight of each evaluation factor and the initial defect degree; and determining the factor grade of each evaluation factor by adopting a preset grade dividing formula based on the grade weight number and the discrete grade of the evaluation factor.
Optionally, before determining the plurality of assessment factors for assessing acetabular bone, the assessment method further comprises: preprocessing historical record data of each evaluation factor of the acetabular bone of the target user by adopting a rough set algorithm, and determining a data discrete table, wherein the preprocessed factor data are stored in the data discrete table; performing entropy weight calculation on the preprocessed factor data by adopting an entropy weight calculation method to obtain an entropy weight of each evaluation factor, and calculating a data characteristic weight of each evaluation factor based on the entropy weight; establishing a set-pair relationship in a grading manner by adopting a set-pair theory analysis algorithm based on each evaluation factor and the factor of the evaluation factor, and determining a data feature vector based on the set-pair relationship; and constructing an acetabular bone defect evaluation model based on the data discrete table, the data feature weight and the data feature vector, wherein the acetabular bone defect evaluation model is used for assisting in evaluating the defect degree of the user's acetabular bone.
Optionally, the step of determining a discrete table of data by preprocessing the historical data of each evaluation factor of the target user's acetabulum bones by using a rough set algorithm includes: acquiring the factor attribute of each evaluation factor to establish an attribute information table, wherein the attribute information table records the corresponding relation among each evaluation factor, the factor attribute and the factor grade; and discretizing the factor attributes in the attribute information table to obtain a data discretization table.
Optionally, the evaluation factor comprises at least one of: horseshoe fossa, acetabulum fossa, anterior column, posterior column, and acetabulum top.
According to another aspect of the embodiments of the present invention, there is also provided an acetabular bone defect assessment device applied to a bone defect degree assessment apparatus for a hip joint, the device including: a first determination unit configured to determine a plurality of evaluation factors for evaluating an acetabular bone; the second determining unit is used for determining the characteristic weight and the initial defect degree of each evaluation factor based on the acetabulum bone image of the target user; a third determining unit, configured to determine a factor level of each evaluation factor based on the feature weight and the initial defect degree; and the evaluation unit is used for dividing the regions based on the factor grades and the grades of all the evaluation factors and evaluating the defect degree of the hip-bone of the target user.
Optionally, the second determining unit includes: the first analysis module is used for analyzing the acetabular bone image to obtain characteristic information of the acetabular bone side; the first determining module is used for determining the information entropy of each evaluation factor by adopting an entropy weight calculation method and calculating the characteristic weight of the evaluation factor based on the information entropy; the second determination module is used for determining the factor grade, the difference degree component and the difference degree component coefficient of each evaluation factor based on the characteristic information; the combination module is used for combining each evaluation factor and the factor grade into a set-pair relation by adopting a set-pair theoretical analysis method; and the quantization processing module is used for quantizing the initial defect degree of the evaluation factor based on the set pair relationship, the difference degree component and the difference degree component coefficient.
Optionally, the third determining unit includes: a third determining module, configured to determine, based on the feature weight of each evaluation factor and the initial defect degree, a level weight number and a discrete level of the evaluation factor; and the fourth determining module is used for determining the factor grade of each evaluation factor by adopting a preset grade dividing formula based on the grade weight number and the discrete grade of the evaluation factor.
Optionally, the device for assessing an acetabular bone defect further comprises: the device comprises a preprocessing unit, a data discrete table and a data analysis unit, wherein the preprocessing unit is used for preprocessing historical record data of each evaluation factor of the acetabulum bone of a target user by adopting a rough set algorithm before determining a plurality of evaluation factors for evaluating the acetabulum bone and determining the data discrete table, and the preprocessed factor data are stored in the data discrete table; the calculation unit is used for performing entropy weight calculation on the preprocessed factor data by adopting an entropy weight calculation method to obtain the entropy weight of each evaluation factor, and calculating the data characteristic weight of each evaluation factor based on the entropy weight; the system comprises a set-pair relationship establishing unit, a set-pair theory analysis unit and a data feature vector determining unit, wherein the set-pair relationship establishing unit is used for establishing a set-pair relationship in a grading manner on the basis of each evaluation factor and the factor of the evaluation factor by adopting a set-pair theory analysis algorithm and determining a data feature vector on the basis of the set-pair relationship; and the model construction unit is used for constructing an acetabular bone defect evaluation model based on the data discrete table, the data feature weight and the data feature vector, wherein the acetabular bone defect evaluation model is used for assisting in evaluating the defect degree of the acetabular bone of the user.
Optionally, the pre-processing unit comprises: the acquisition module is used for acquiring the factor attribute of each evaluation factor to establish an attribute information table, wherein the attribute information table records the corresponding relation among each evaluation factor, the factor attribute and the factor grade; and the discretization processing module is used for performing discretization processing on the factor attributes in the attribute information table to obtain a data discretization table.
Optionally, the evaluation factor comprises at least one of: horseshoe fossa, acetabulum fossa, anterior column, posterior column, and acetabulum top.
According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform any one of the above methods of assessing acetabular bone defects via execution of the executable instructions.
According to another aspect of the embodiment of the present invention, there is further provided a storage medium, the storage medium includes a stored program, wherein when the program runs, the apparatus on which the storage medium is located is controlled to execute any one of the above methods for assessing acetabular bone defects.
In the embodiment of the invention, a plurality of evaluation factors for evaluating the acetabular bone are determined, then the characteristic weight and the initial defect degree of each evaluation factor are determined based on the acetabular bone image of the target user, then the factor grade of each evaluation factor is determined based on the characteristic weight and the initial defect degree, and finally the defect degree of the acetabular bone of the target user is evaluated by dividing the interval based on the factor grades and the grades of all the evaluation factors. In the embodiment, different degrees of acetabular bone defects can be analyzed and evaluated, the degree of acetabular bone side bone defects can be fully evaluated, and the most appropriate treatment mode is provided for patients according to different bone defect degrees, so that the technical problems that most of acetabular bone defect degrees are evaluated manually by experience in related technologies, evaluation results are large in difference, and accuracy is reduced are solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a flow chart of an alternative method of evaluating an acetabular bone defect according to an embodiment of the invention;
figure 2 is a schematic view of an alternative acetabular bone defect assessment device according to embodiments of the invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
To facilitate understanding of the invention by those skilled in the art, some terms or nouns referred to in the embodiments of the invention are explained below:
the rough set algorithm (RS for short) and the tool for processing the uncertain problems can effectively reduce the subjectivity and the fuzziness of the evaluation result, and can directly analyze and process the data without considering any prior information.
An entropy weight calculation method (EW for short) is an objective weight calculation method, and the entropy weight of each index is calculated through information entropy, so that a better evaluation result can be obtained.
And (3) a set pair theoretical analysis method (SPA for short) forms a set pair by the evaluation factors and the evaluation grade, so that the characteristic weighted data is vectorized.
The embodiment of the invention can construct an RS-EW-SPA model architecture, and introduces a rough set algorithm (RS), an entropy weight calculation method (EW) and a set pair theoretical analysis method (SPA) into the graded evaluation of the acetabular bone defect.
The acetabular bone defect evaluation method provided by the following embodiment of the invention can be applied to environments such as acetabular bone image processing, hip joint defect degree evaluation, hip joint revision and the like, so as to provide a proper processing method for bone defect patients and perform grading evaluation on different degrees of acetabular bone defects. The invention designs an RS-EW-SPA model, introduces a rough set algorithm (RS), an entropy weight calculation method (EW) and a set pair theoretical analysis method (SPA) into the graded evaluation of the acetabular bone defect, utilizes RS to preprocess data, utilizes the EW to determine index weight and utilizes SPA to quantize data, and establishes a data graded evaluation model reflecting the acetabular bone defect degree, thereby providing decision support for the selection of a processing mode. The invention is illustrated below with reference to various examples.
Example one
In accordance with an embodiment of the present invention, there is provided an embodiment of a method for assessing acetabular bone defects, it being noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system, such as a set of computer-executable instructions, and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than here.
The embodiment of the invention provides an acetabular bone defect assessment method, which is applied to bone defect degree assessment equipment of hip joints.
Fig. 1 is a flow chart of an alternative method of evaluating an acetabular bone defect according to an embodiment of the invention, as shown in fig. 1, including the steps of:
step S102, determining a plurality of evaluation factors for evaluating the acetabular bone;
step S104, determining the characteristic weight and the initial defect degree of each evaluation factor based on the acetabulum bone image of the target user;
step S106, determining the factor grade of each evaluation factor based on the feature weight and the initial defect degree;
and step S108, dividing the regions based on the factor grades and the grades of all the evaluation factors, and evaluating the defect degree of the acetabular bones of the target user.
Through the steps, a plurality of evaluation factors for evaluating the acetabular bone can be determined firstly, then the characteristic weight and the initial defect degree of each evaluation factor are determined based on the acetabular bone image of the target user, then the factor grade of each evaluation factor can be determined based on the characteristic weight and the initial defect degree, and finally the defect degree of the acetabular bone of the target user can be evaluated by dividing the interval based on the factor grades and the grades of all the evaluation factors. In the embodiment, different degrees of acetabular bone defects can be analyzed and evaluated, the degree of acetabular bone side bone defects can be fully evaluated, and the most appropriate treatment mode is provided for patients according to different bone defect degrees, so that the technical problems that most of acetabular bone defect degrees are evaluated manually by experience in related technologies, evaluation results are large in difference, and accuracy is reduced are solved.
The present invention will be described in detail with reference to the above steps.
In an alternative embodiment of the present invention, before determining the plurality of assessment factors for assessing the acetabular bone, the assessment method further comprises: preprocessing historical record data of each evaluation factor of the acetabular bone of the target user by adopting a rough set algorithm, and determining a data discrete table, wherein the preprocessed factor data are stored in the data discrete table; performing entropy weight calculation on the preprocessed factor data by adopting an entropy weight calculation method to obtain an entropy weight of each evaluation factor, and calculating a data characteristic weight of each evaluation factor based on the entropy weight; establishing a set-pair relationship in a grading manner based on each evaluation factor and the factor of the evaluation factor by adopting a set-pair theoretical analysis algorithm, and determining a data feature vector based on the set-pair relationship; and constructing an acetabular bone defect evaluation model based on the data discrete table, the data feature weight and the data feature vector, wherein the acetabular bone defect evaluation model is used for assisting in evaluating the defect degree of the acetabular bone of the user.
The acetabular bone defect evaluation model can be understood as an RS-EW-SPA model, and historical record data of each evaluation factor of acetabular bone defect is preprocessed through a rough set algorithm to determine a data discrete table; performing entropy weight calculation on the preprocessed data by using an entropy weight calculation method according to the index classification interval to obtain a data characteristic weight; and analyzing the data characteristic vector according to the set-to-set theoretical multivariate union coefficient by using a set-to-set theoretical analysis method so as to construct an acetabular bone defect evaluation model.
When the acetabular bone defect model is constructed, the method comprises three steps of data preprocessing, feature weighting and feature vectorization.
(1) Data pre-processing
And preprocessing the historical record data by using a rough set algorithm, and processing the local historical record data into data which can be used for characteristic weighting.
Optionally, the step of preprocessing the historical data of each evaluation factor of the target user acetabulum bone by adopting a rough set algorithm and determining a data discrete table comprises the following steps: acquiring the factor attribute of each evaluation factor to establish an attribute information table, wherein the attribute information table records the corresponding relation among each evaluation factor, the factor attribute and the factor grade; and discretizing the factor attributes in the attribute information table to obtain a data discretization table.
The rough set algorithm (RS) is a mathematical tool for processing uncertain problems theoretically, can effectively reduce subjectivity and fuzziness of an evaluation result, and can directly analyze and process data without considering any prior information, specifically:
1) establishing a knowledge base: the actual attributes of each evaluation factor are utilized to form an attribute information table, a column of indexes corresponds to a column of information levels, and one table is a defined series of level relations;
2) establishing a decision table: the factor attribute of the information table is discretized according to the decision attribute to form a discretization table, so that the original complex data is replaced by simple numbers, and convenience is provided for the following data operation.
(2) Feature weighting
The discrete table obtained after data preprocessing is used as a decision basis for data feature weighting and feature vectorization. In order to show the importance degree and the effect of each evaluation factor in the whole evaluation system, the weight coefficient of each evaluation factor needs to be determined according to the influence of each evaluation factor. For the same set of evaluation factor data, if the weighting coefficients are different, the evaluation conclusion obtained will be different.
An entropy weight calculation method (EW) is an objective weight calculation method, and the entropy weight of each index is calculated through information entropy, so that a better evaluation result can be obtained.
Determining weight by using a rough set-entropy weight calculation method, and according to the entropy theorem, when the system is in Y different states, and the probability of each state is fiv(iv — 1, 2, 3, …, n), the entropy of the system is defined as: for T indexes, within the regional system of Y classified objects, the entropy value H of the v indexvThe calculation formula of (2) is as follows:
Figure BDA0002334356690000071
Figure BDA0002334356690000072
wherein,
Figure BDA0002334356690000073
standardizing the original data set to obtain a matrix aiv′：
Figure BDA0002334356690000074
In the formula, aiv' is a matrix after data is standardized;
r is the original data; r _ max, R _ min are the maximum and minimum values of the original data set, respectively.
The entropy weight of the v-th index (v ═ 0, 1, 2, …, n) is:
Figure BDA0002334356690000075
the entropy value is used as weight for calculation, the size of the entropy has a direct relation with a target user, and the action degree of the evaluation factor for providing information quantity is reflected. When the difference of the entropy values of the evaluation factor v on each evaluation object is large, the smaller the entropy value is, the larger the entropy weight is, which indicates that the evaluation factor v provides useful information for decision, and an entropy weight calculation method is used for calculating the data which is subjected to rough set processing in the prior art, so as to provide guidance for calculating the data evaluation weight.
(3) Feature vectorization
And establishing set-pair connection for the data grading evaluation calculation under the set-pair theory through the entropy weight obtained by the data characteristic weighting calculation, wherein the multi-element connection coefficient evolves in the set-pair theory according to the three-element connection coefficient in the connection degree, and is a refined depiction of the same state, different state and opposite state.
According to an analysis method of set-to-theoretical multivariate joint coefficients (namely, a set-to-theoretical analysis method, SPA), the evaluation factors and the evaluation levels form a set pair, so that the data features after feature weighting are vectorized, and a multivariate relation relational expression, namely a quantitative formula, is established:
u ═ a + b1i1+ … + bnin + cj; wherein b1, b2 and … bn are difference component coefficients, i1, i2 and … in are difference component coefficients;
aiming at the evaluation factors, establishing an evaluation grade division formula of the multivariate union coefficient:
dn ═ aw0+ b1w1+ … + b10wi-1+ cwi; where wi is the number of rank weights, and a, bi, and c represent discrete ranks.
Various factors evaluated for acetabular bone defects include, but are not limited to: the defect degree of characteristics of the acetabulum such as a horseshoe fossa, an acetabulum fossa, a front column, a rear column, an acetabulum top and the like.
In the present example, the classification number of three grades is determined according to the actual condition and the weight of the defect degree of the horseshoe fossa, the acetabulum fossa, the anterior column, the posterior column and the acetabulum top at the acetabulum:
first grade D1：1≤D1≤3w0+w1+…+w4；
Second grade D2：3w0+w1+…+w4≤D2≤6w0+w1+…+w4；
Third grade D3：6w0+w1+…+w4≤D3≤9w0+w1+…+w4；
And calculating the grade value of each influence factor according to a quantization formula, and dividing the grade value into corresponding grade intervals to finish the grading evaluation of all evaluation factors.
Step S102, determining a plurality of evaluation factors for evaluating the acetabular bone.
Alternatively, the evaluation factors include, but are not limited to: horseshoe fossa, acetabulum fossa, anterior column, posterior column, and acetabulum top.
And step S104, determining the characteristic weight and the initial defect process of each evaluation factor based on the acetabulum bone image of the target user.
In an alternative embodiment of the present invention, the step of determining the feature weight and the initial defect degree of each evaluation factor includes: analyzing the acetabular bone image to obtain characteristic information of the acetabular bone side; determining the information entropy of each evaluation factor by adopting an entropy weight calculation method, and calculating the characteristic weight of each evaluation factor based on the information entropy; determining a factor grade, a difference component and a difference component coefficient of each evaluation factor based on the characteristic information; combining each evaluation factor and factor grade into a set-pair relation by adopting a set-pair theoretical analysis method; and quantitatively processing the initial defect degree of the evaluation factor based on the set pair relationship, the difference degree component and the difference degree component coefficient.
The set-pair relationship indicates that each evaluation factor and the corresponding evaluation grade are combined into a pair of vector relationships, so that the set-pair relationship of all the evaluation factors is established.
In the embodiment of the invention, the evaluation factors and the evaluation grades are combined into a set pair according to a set pair theory analysis method, so that the characteristic weighted data is vectorized, and a multivariate relation formula, namely a quantization formula, is established:
u ═ a + b1i1+ … + bnin + cj; wherein b1, b2 and … bn are difference component coefficients, i1, i2 and … in are difference component coefficients;
and step S106, determining the factor grade of each evaluation factor based on the feature weight and the initial defect degree.
In the embodiment of the present invention, the step of determining the factor grade of each evaluation factor based on the feature weight and the initial defect degree includes: determining the grade weight number and the discrete grade of each evaluation factor based on the characteristic weight and the initial defect degree of each evaluation factor; and determining the factor grade of each evaluation factor by adopting a preset grade dividing formula based on the grade weight number and the discrete grade of the evaluation factor.
Aiming at the evaluation factors, establishing an evaluation grade division formula of the multivariate union coefficient:
dn ═ aw0+ b1w1+ … + b10wi-1+ cwi; where wi is the number of the grade weights, a, bi, c represent discrete grades, and the factor grade of each evaluation factor is determined using the evaluation grade division formula.
The factor grade can determine the grade corresponding to the evaluation factor according to the acetabulum bone evaluation result of each patient, the grade number of the factor grade is not limited, for example, the factor grade is divided into three grades, then the grade value of each influencing factor is calculated according to a quantitative formula and divided into corresponding grade intervals, and the grading evaluation of all indexes is completed.
And step S108, dividing the regions based on the factor grades and the grades of all the evaluation factors, and evaluating the defect degree of the acetabular bones of the target user.
The embodiment of the invention can determine the factor grade of each evaluation factor by using an acetabular bone defect evaluation model, then position the grade division interval in which the factor grade of the evaluation factor is positioned, and determine the acetabular bone defect degree by integrating the factor grades of all the evaluation factors and the grade division intervals, for example, dividing the acetabular bone defect into three grade intervals (mild defect, moderate defect and severe defect) to obtain defect degree evaluation.
The invention is described in detail below with reference to an alternative embodiment.
The following example provides an alternative method of assessing an acetabular bone defect comprising:
s1, determining a plurality of evaluation factors, preprocessing the acetabular bone data by adopting a rough set algorithm, and establishing a knowledge base and a decision table;
s2, performing feature weighting calculation by using an entropy weight calculation method to obtain a factor weight set;
s3, performing feature vectorization processing by adopting a set-pair theoretical analysis method to obtain a multi-element relation and an evaluation fan;
and S4, determining the result of evaluating the acetabular bone defect.
Example two
Fig. 2 is a schematic view of an alternative acetabular bone defect evaluation device according to an embodiment of the present invention, applied to a bone defect degree evaluation apparatus for hip joints, as shown in fig. 2, the evaluation device including: a first determination unit 22, a second determination unit 24, a third determination unit 26, an evaluation unit 28, wherein,
a first determination unit 22 for determining a plurality of evaluation factors for evaluating the acetabular bone;
the second determining unit 24 is configured to determine a feature weight and an initial defect degree of each evaluation factor based on the acetabular bone image of the target user;
a third determining unit 26, configured to determine a factor level of each evaluation factor based on the feature weight and the initial defect degree;
and an evaluation unit 28 for dividing the regions based on the factor grades and the grades of all evaluation factors to evaluate the defect degree of the hip-bone of the target user.
The above-mentioned acetabular bone defect assessment device can determine a plurality of assessment factors for assessing acetabular bones by the first determination unit 22, then determine the characteristic weight and the initial defect degree of each assessment factor based on the acetabular bone image of the target user by the second determination unit 24, then determine the factor grade of each assessment factor based on the characteristic weight and the initial defect degree by the third determination unit 26, and finally assess the defect degree of the acetabular bones of the target user by the assessment unit 28 based on the factor grades and grades of all the assessment factors. In the embodiment, different degrees of acetabular bone defects can be analyzed and evaluated, the degree of acetabular bone side bone defects can be fully evaluated, and the most appropriate treatment mode is provided for patients according to different bone defect degrees, so that the technical problems that most of acetabular bone defect degrees are evaluated manually by experience in related technologies, evaluation results are large in difference, and accuracy is reduced are solved.
Optionally, the second determining unit includes: the first analysis module is used for analyzing the acetabular bone image to obtain characteristic information of the acetabular bone side; the first determining module is used for determining the information entropy of each evaluation factor by adopting an entropy weight calculation method and calculating the characteristic weight of the evaluation factor based on the information entropy; the second determination module is used for determining the factor grade, the difference degree component and the difference degree component coefficient of each evaluation factor based on the characteristic information; the combination module is used for combining each evaluation factor and the factor grade into a set-pair relation by adopting a set-pair theoretical analysis method; and the quantization processing module is used for quantizing the initial defect degree of the evaluation factor based on the set pair relationship, the difference degree component and the difference degree component coefficient.
In an alternative embodiment of the present invention, the third determining unit includes: the third determining module is used for determining the grade weight number and the discrete grade of each evaluation factor based on the characteristic weight and the initial defect degree of each evaluation factor; and the fourth determining module is used for determining the factor grade of each evaluation factor by adopting a preset grade dividing formula based on the grade weight number and the discrete grade of the evaluation factor.
Alternatively, the device for evaluating an acetabular bone defect further comprises: the device comprises a preprocessing unit, a data discrete table and a data analysis unit, wherein the preprocessing unit is used for preprocessing historical record data of each evaluation factor of the acetabulum bone of a target user by adopting a rough set algorithm before determining a plurality of evaluation factors for evaluating the acetabulum bone and determining the data discrete table, and the preprocessed factor data are stored in the data discrete table; the calculation unit is used for performing entropy weight calculation on the preprocessed factor data by adopting an entropy weight calculation method to obtain the entropy weight of each evaluation factor, and calculating the data characteristic weight of each evaluation factor based on the entropy weight; the set-pair relationship establishing unit is used for establishing a set-pair relationship in a grading manner on the basis of each evaluation factor and the factor of the evaluation factor by adopting a set-pair theoretical analysis algorithm and determining a data characteristic vector on the basis of the set-pair relationship; and the model building unit is used for building an acetabular bone defect evaluation model based on the data discrete table, the data feature weight and the data feature vector, wherein the acetabular bone defect evaluation model is used for assisting in evaluating the defect degree of the acetabular bone of the user.
In an alternative embodiment of the invention, the pre-processing unit comprises: the acquisition module is used for acquiring the factor attribute of each evaluation factor to establish an attribute information table, wherein the attribute information table records the corresponding relation among each evaluation factor, the factor attribute and the factor grade; and the discretization processing module is used for performing discretization processing on the factor attributes in the attribute information table to obtain a data discretization table.
Optionally, the evaluation factor comprises at least one of: horseshoe fossa, acetabulum fossa, anterior column, posterior column, and acetabulum top.
The above-mentioned acetabular bone defect assessment device may further include a processor and a memory, and the above-mentioned first determination unit 22, second determination unit 24, third determination unit 26, assessment unit 28, etc. are stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to implement the corresponding functions.
The processor comprises a kernel, and the kernel calls a corresponding program unit from the memory. The kernel can be provided with one or more than one, and the defect degree of the target user acetabulum bone is evaluated by adjusting the parameters of the kernel.
The memory may include volatile memory in a computer readable medium, Random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip.
According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including: a processor; and a memory for storing executable instructions for the processor; wherein the processor is configured to perform any one of the above methods of assessing acetabular bone defects via execution of executable instructions.
According to another aspect of the embodiment of the present invention, there is further provided a storage medium, where the storage medium includes a stored program, and when the program runs, the apparatus on which the storage medium is located is controlled to execute any one of the above methods for assessing acetabular bone defects.
The present application further provides a computer program product adapted to perform a program for initializing the following method steps when executed on a data processing device: determining a plurality of assessment factors for assessing an acetabular bone; determining the characteristic weight and the initial defect degree of each evaluation factor based on the acetabulum bone image of the target user; determining the factor grade of each evaluation factor based on the feature weight and the initial defect degree; and dividing the regions based on the factor grades and the grades of all the evaluation factors to evaluate the defect degree of the acetabular bones of the target users.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.

Claims (10)

1. An evaluation method of acetabular bone defect, characterized by being applied to a bone defect degree evaluation device of a hip joint, the evaluation method comprising:
determining a plurality of assessment factors for assessing an acetabular bone;
determining the characteristic weight and the initial defect degree of each evaluation factor based on the acetabulum bone image of the target user;
determining the factor grade of each evaluation factor based on the feature weight and the initial defect degree;
and dividing the regions based on the factor grades and the grades of all the evaluation factors to evaluate the defect degree of the acetabular bones of the target users.
2. The evaluation method according to claim 1, wherein the step of determining the feature weight and the initial defect degree of each evaluation factor comprises:
analyzing the acetabular bone image to obtain characteristic information of the acetabular bone side;
determining the information entropy of each evaluation factor by adopting an entropy weight calculation method, and calculating the characteristic weight of each evaluation factor based on the information entropy;
determining a factor grade, a difference degree component and a difference degree component coefficient of each evaluation factor based on the characteristic information;
combining each evaluation factor and factor grade into a set-pair relation by adopting a set-pair theoretical analysis method;
and quantizing the initial defect degree of the evaluation factor based on the set pair relationship, the difference degree component and the difference degree component coefficient.
3. The method of claim 1, wherein the step of determining the factor rank of each evaluation factor based on the feature weight and the initial defect degree comprises:
determining the grade weight number and the discrete grade of each evaluation factor based on the characteristic weight of each evaluation factor and the initial defect degree;
and determining the factor grade of each evaluation factor by adopting a preset grade dividing formula based on the grade weight number and the discrete grade of the evaluation factor.
4. The assessment method of claim 1, wherein prior to determining a plurality of assessment factors for assessing acetabular bone, the assessment method further comprises:
preprocessing historical record data of each evaluation factor of the acetabular bone of the target user by adopting a rough set algorithm, and determining a data discrete table, wherein the preprocessed factor data are stored in the data discrete table;
performing entropy weight calculation on the preprocessed factor data by adopting an entropy weight calculation method to obtain an entropy weight of each evaluation factor, and calculating a data characteristic weight of each evaluation factor based on the entropy weight;
establishing a set-pair relationship in a grading manner by adopting a set-pair theory analysis algorithm based on each evaluation factor and the factor of the evaluation factor, and determining a data feature vector based on the set-pair relationship;
and constructing an acetabular bone defect evaluation model based on the data discrete table, the data feature weight and the data feature vector, wherein the acetabular bone defect evaluation model is used for assisting in evaluating the defect degree of the user's acetabular bone.
5. The assessment method according to claim 4, wherein the step of pre-processing the historical data of each assessment factor of the target user's acetabulum bones by using a rough set algorithm to determine a data discrete table comprises:
acquiring the factor attribute of each evaluation factor to establish an attribute information table, wherein the attribute information table records the corresponding relation among each evaluation factor, the factor attribute and the factor grade;
and discretizing the factor attributes in the attribute information table to obtain a data discretization table.
6. The evaluation method of claim 1, wherein the evaluation factor comprises at least one of: horseshoe fossa, acetabulum fossa, anterior column, posterior column, and acetabulum top.
7. An acetabular bone defect assessment device to be applied to a bone defect degree assessment apparatus for a hip joint, comprising:
a first determination unit configured to determine a plurality of evaluation factors for evaluating an acetabular bone;
the second determining unit is used for determining the characteristic weight and the initial defect degree of each evaluation factor based on the acetabulum bone image of the target user;
a third determining unit, configured to determine a factor level of each evaluation factor based on the feature weight and the initial defect degree;
and the evaluation unit is used for dividing the regions based on the factor grades and the grades of all the evaluation factors and evaluating the defect degree of the hip-bone of the target user.
8. The evaluation apparatus according to claim 7, wherein the second determination unit includes:
the first analysis module is used for analyzing the acetabular bone image to obtain characteristic information of the acetabular bone side;
the first determining module is used for determining the information entropy of each evaluation factor by adopting an entropy weight calculation method and calculating the characteristic weight of the evaluation factor based on the information entropy;
the second determination module is used for determining the factor grade, the difference degree component and the difference degree component coefficient of each evaluation factor based on the characteristic information;
the combination module is used for combining each evaluation factor and the factor grade into a set-pair relation by adopting a set-pair theoretical analysis method;
and the quantization processing module is used for quantizing the initial defect degree of the evaluation factor based on the set pair relationship, the difference degree component and the difference degree component coefficient.
9. An electronic device, comprising:
a processor; and
a memory for storing executable instructions of the processor;
wherein the processor is configured to perform the method of assessing an acetabular bone defect of any one of claims 1-6 via execution of the executable instructions.
10. A storage medium comprising a stored program, wherein the program is executed to control a device on which the storage medium is located to perform the method for assessing a defect in an acetabular bone according to any one of claims 1 to 6.
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