CN108335599B - Operation model training method based on three-dimensional modeling image technology - Google Patents
Operation model training method based on three-dimensional modeling image technology Download PDFInfo
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Abstract
A surgical model training method based on a three-dimensional modeling image technology comprises the following steps: s1, acquiring three-dimensional image information of different tissues and organs in different body types, ages and sexes, and performing key point calibration on the three-dimensional image information to obtain a three-dimensional training model set comprising corresponding different three-dimensional training model information; s2, establishing triggering performance information of key points of the three-dimensional training model information; generating a random burst condition instance set; s3, generating instrument control conversion parameters according to different operation types corresponding to different tissues and organs; acquiring operation type training request information of a user, and determining corresponding instrument control conversion parameters according to the operation type training request information; and S4, extracting three-dimensional training model information from the three-dimensional training model set as an object of surgery simulation training, receiving operation information of a user, and converting the operation information into operation information of the three-dimensional training model information through instrument control conversion parameters according to the operation information of the user.
Description
Technical Field
The invention relates to the technical field of operation simulation training, in particular to an operation model training method based on a three-dimensional modeling image technology.
Background
The existing surgical operation training often occurs in medical colleges and subsidiary hospitals of the medical colleges, and because the training opportunities of clinical operations are limited, medical trainees can not obtain good training. Some operation training devices also appear in the prior art, but real operation scenes cannot be simulated completely, and most importantly, one operation training device can only adapt to one type of operation after being used for a long time, the level cannot be improved again in one type of operation training, and the existing operation simulation training method is very teaching, and various sudden conditions in the operation process cannot be simulated really.
Disclosure of Invention
In view of this, the present invention provides a method for training an operation model based on a three-dimensional modeling image technology.
A surgical model training method based on a three-dimensional modeling image technology comprises the following steps:
s1, acquiring three-dimensional image information of different tissues and organs in different body types, ages and sexes, and performing key point calibration on the three-dimensional image information to obtain a three-dimensional training model set comprising corresponding different three-dimensional training model information;
s2, establishing triggering performance information of key points of the three-dimensional training model information; generating a random burst condition instance set;
s3, generating instrument control conversion parameters according to different operation types corresponding to different tissues and organs; acquiring operation type training request information of a user, and determining corresponding instrument control conversion parameters according to the operation type training request information;
s4, extracting three-dimensional training model information from the three-dimensional training model set as an object of surgery simulation training, receiving operation information of a user, and converting the operation information into operation information of the three-dimensional training model information through instrument control conversion parameters according to the operation information of the user;
s5, matching and recording the operation result of the user according to the triggering performance information of the key points of the three-dimensional training model information to obtain a first record set;
s6, randomly extracting a random burst condition example from the random burst condition example set, generating burst triggering expression information according to the random burst condition example, transforming the three-dimensional training model to obtain burst three-dimensional training model information, converting the operation information of the user into operation information of the burst three-dimensional training model information through an instrument control conversion parameter, and matching and recording the operation result of the user according to the burst triggering expression information of the burst three-dimensional training model information to obtain a second record set;
and S7, generating a model training evaluation result on the hand of the user according to the first record set and the second record set.
In the surgical model training method based on the three-dimensional modeling image technology, the step S1 includes:
acquiring image information of different tissues and organs corresponding to different angles in different body types, ages and sexes;
establishing corresponding three-dimensional image information according to the image information of different angles, wherein the three-dimensional image information is represented by three-dimensional coordinate points;
and carrying out key point calibration on the corresponding three-dimensional coordinate points according to the probability and the weight distribution of the tissue and the organ corresponding to different positions and depths in different operation simulation training types.
In the surgical model training method based on the three-dimensional modeling image technology of the invention,
the triggering performance information of the key points for establishing the three-dimensional training model information in step S2 includes:
establishing a trigger performance information sequence, wherein the trigger performance information sequence comprises: sequence information, processing time information, position information, precision information, and deformation threshold information;
configuring a mapping relation between a trigger expression information sequence and an operation simulation training type;
and performing serial code conversion on the value of the mapping relation and the trigger performance information sequence, and configuring the serial code value to a three-dimensional coordinate point after the key point is calibrated.
In the surgical model training method based on the three-dimensional modeling image technology of the invention,
the step S2 of generating the random burst condition instance set includes:
configuring burst implementation of a surgery simulation training type, and configuring control parameters corresponding to each burst instance, wherein the control parameters comprise: three-dimensional training model deformation control parameters and three-dimensional training model expansion control parameters.
The beneficial technical effects are as follows: compared with the prior art, the invention can realize that: performing simulation training on different operation types according to three-dimensional image information of different tissues and organs in different body types, ages and sexes; and by introducing the random burst condition example set, various burst conditions can be simulated in the surgical training process, and the capability of a user for coping with the burst conditions is effectively trained.
Drawings
Fig. 1 is a flowchart of a surgical model training method based on a three-dimensional modeling image technology according to an embodiment of the present invention.
Detailed Description
As shown in fig. 1, in an embodiment of the present invention, a method for training a surgical model based on a three-dimensional modeling image technology includes the following steps:
s1, three-dimensional image information of different tissues and organs in different body types, ages and sexes is obtained, and key point calibration is carried out on the three-dimensional image information to obtain a three-dimensional training model set comprising corresponding different three-dimensional training model information.
Optionally, the step S1 includes:
acquiring image information of different tissues and organs corresponding to different angles in different body types, ages and sexes;
establishing corresponding three-dimensional image information according to the image information of different angles, wherein the three-dimensional image information is represented by three-dimensional coordinate points;
and carrying out key point calibration on the corresponding three-dimensional coordinate points according to the probability and the weight distribution of the tissue and the organ corresponding to different positions and depths in different operation simulation training types.
In the preferred embodiment of the present invention, the positions of the surgical instruments contacting the organs are different due to different etiologies of different tissues and organs in the surgical training, and the probability of the depth is used to represent the contact possibility of the surgical instruments and the organs at different positions, and the weight distribution refers to the influence on the whole surgical training when the surgery is applied to the organs. Therefore, the three-dimensional training model information formed by the three-dimensional coordinate points after the key points are calibrated is beneficial to the precision of training results of different operation types, and is particularly suitable for operation training scenes based on the virtual reality technology.
S2, establishing triggering performance information of key points of the three-dimensional training model information; and generates a set of random burst condition instances.
Alternatively,
the triggering performance information of the key points for establishing the three-dimensional training model information in step S2 includes:
establishing a trigger performance information sequence, wherein the trigger performance information sequence comprises: sequence information, processing time information, position information, precision information, and deformation threshold information;
configuring a mapping relation between a trigger expression information sequence and an operation simulation training type;
and performing serial code conversion on the value of the mapping relation and the trigger performance information sequence, and configuring the serial code value to a three-dimensional coordinate point after the key point is calibrated.
The step S2 of generating the random burst condition instance set includes:
configuring burst implementation of a surgery simulation training type, and configuring control parameters corresponding to each burst instance, wherein the control parameters comprise: three-dimensional training model deformation control parameters and three-dimensional training model expansion control parameters.
The three-dimensional training model deformation control parameters mean that the shape, the size and the like of the three-dimensional training model are changed; the three-dimensional training model expansion control parameters refer to that in addition to the three-dimensional training model, another three-dimensional training model is added, and the additionally added three-dimensional training model also needs to be processed by a user.
S3, generating instrument control conversion parameters according to different operation types corresponding to different tissues and organs; acquiring operation type training request information of a user, and determining corresponding instrument control conversion parameters according to the operation type training request information;
optionally, the determining a model of the corresponding instrument control conversion parameter according to the surgical type training request information includes:
By implementing the preferred embodiment, the control strength applied to the instrument in the direction of the degree of freedom of the user can be accurately converted into the operation of the instrument on the organ by the user in the surgical training, and the misjudgment of the surgical training result of the user due to too large error in the conversion process can be avoided.
S4, extracting three-dimensional training model information from the three-dimensional training model set as an object of surgery simulation training, receiving operation information of a user, and converting the operation information into operation information of the three-dimensional training model information through instrument control conversion parameters according to the operation information of the user;
s5, matching and recording the operation result of the user according to the triggering performance information of the key points of the three-dimensional training model information to obtain a first record set;
s6, randomly extracting a random burst condition example from the random burst condition example set, generating burst triggering expression information according to the random burst condition example, transforming the three-dimensional training model to obtain burst three-dimensional training model information, converting the operation information of the user into operation information of the burst three-dimensional training model information through an instrument control conversion parameter, and matching and recording the operation result of the user according to the burst triggering expression information of the burst three-dimensional training model information to obtain a second record set;
step S6 is a major improvement point in the embodiments of the present invention, where different random burst condition instances are configured in the random burst condition instance set by setting the random burst condition instance set, and the different random burst condition instances transform the three-dimensional training model to obtain burst three-dimensional training model information, and at the same time, may also generate burst trigger performance information. For example, one random burst condition example is excessive bleeding, which affects the color of organs and forms a blood pool around the organs, which affects the shape of organ models, and burst three-dimensional training model information is obtained by adding the random burst condition example, which can greatly affect the performance of users during surgical training and is closer to the real surgical scene.
And S7, generating a model training evaluation result on the hand of the user according to the first record set and the second record set.
Compared with the prior art, the embodiment of the invention can subdivide the operation training process through three-dimensional modeling and key point calibration technologies, not only simply carry out three-dimensional digitization on organs, but also establish an accurate corresponding relation between the operation of a user and the change of the organs, thereby carrying out accurate evaluation on the training of the user.
Persons skilled in the art can know that both organs and instruments can be realized in a three-dimensional modeling mode, and the operation of a user can acquire parameters through sensing devices such as a force feedback device and a speed acquisition device, so that the virtual reality modeling is realized.
The beneficial technical effects are as follows: compared with the prior art, the invention can realize that: performing simulation training on different operation types according to three-dimensional image information of different tissues and organs in different body types, ages and sexes; and by introducing the random burst condition example set, various burst conditions can be simulated in the surgical training process, and the capability of a user for coping with the burst conditions is effectively trained.
It is understood that various other changes and modifications may be made by those skilled in the art based on the technical idea of the present invention, and all such changes and modifications should fall within the protective scope of the claims of the present invention.
Claims (2)
1. A surgical model training method based on a three-dimensional modeling image technology is characterized by comprising the following steps:
s1, acquiring three-dimensional image information of different tissues and organs in different body types, ages and sexes, and performing key point calibration on the three-dimensional image information to obtain a three-dimensional training model set comprising corresponding different three-dimensional training model information;
s2, establishing triggering performance information of key points of the three-dimensional training model information; generating a random burst condition instance set;
s3, generating instrument control conversion parameters according to different operation types corresponding to different tissues and organs; acquiring operation type training request information of a user, and determining corresponding instrument control conversion parameters according to the operation type training request information; the model for determining the corresponding instrument control conversion parameter according to the operation type training request information comprises the following steps:
s4, extracting three-dimensional training model information from the three-dimensional training model set as an object of surgery simulation training, receiving operation information of a user, and converting the operation information into operation information of the three-dimensional training model information through instrument control conversion parameters according to the operation information of the user;
s5, matching and recording the operation result of the user according to the triggering performance information of the key points of the three-dimensional training model information to obtain a first record set;
s6, randomly extracting a random burst condition example from the random burst condition example set, generating burst triggering expression information according to the random burst condition example, transforming the three-dimensional training model to obtain burst three-dimensional training model information, converting the operation information of the user into operation information of the burst three-dimensional training model information through an instrument control conversion parameter, and matching and recording the operation result of the user according to the burst triggering expression information of the burst three-dimensional training model information to obtain a second record set;
s7, generating a model training evaluation result on the hand of the user according to the first record set and the second record set;
the step S1 includes:
acquiring image information of different tissues and organs corresponding to different angles in different body types, ages and sexes;
establishing corresponding three-dimensional image information according to the image information of different angles, wherein the three-dimensional image information is represented by three-dimensional coordinate points;
performing key point calibration on corresponding three-dimensional coordinate points according to the probability and weight distribution of different positions and depths corresponding to tissues and organs in different operation simulation training types;
the triggering performance information of the key points for establishing the three-dimensional training model information in step S2 includes:
establishing a trigger performance information sequence, wherein the trigger performance information sequence comprises: sequence information, processing time information, position information, precision information, and deformation threshold information;
configuring a mapping relation between a trigger expression information sequence and an operation simulation training type;
and performing serial code conversion on the value of the mapping relation and the trigger performance information sequence, and configuring the serial code value to a three-dimensional coordinate point after the key point is calibrated.
2. The surgical model training method based on three-dimensional modeling image technology according to claim 1,
the step S2 of generating the random burst condition instance set includes: configuring burst implementation of a surgery simulation training type, and configuring control parameters corresponding to each burst instance, wherein the control parameters comprise: deformation control parameters of the three-dimensional training model and expansion control parameters of the three-dimensional training model; the three-dimensional training model deformation control parameters mean that the shape, the size and the like of the three-dimensional training model are changed; the three-dimensional training model expansion control parameters refer to that in addition to the three-dimensional training model, another three-dimensional training model is added, and the additionally added three-dimensional training model also needs to be processed by a user.
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| CN112734704B (en) * | 2020-12-29 | 2023-05-16 | 上海索验智能科技有限公司 | Skill training evaluation method under neural network machine learning recognition objective lens |
| CN114121218A (en) * | 2021-11-26 | 2022-03-01 | 中科麦迪人工智能研究院(苏州)有限公司 | Virtual scene construction method, device, equipment and medium applied to operation |
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| CN105825752A (en) * | 2016-04-22 | 2016-08-03 | 吉林大学 | Force feedback device-based virtual corneal surgery training system |
| CN107067856A (en) * | 2016-12-31 | 2017-08-18 | 歌尔科技有限公司 | A kind of medical simulation training system and method |
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| CN103961179B (en) * | 2014-04-09 | 2016-04-27 | 深圳先进技术研究院 | Surgical instrument movement analogy method |
| CN204029245U (en) * | 2014-08-01 | 2014-12-17 | 卓思生命科技有限公司 | A surgical simulation system |
| CN106297471A (en) * | 2016-10-25 | 2017-01-04 | 深圳市科创数字显示技术有限公司 | The removable cornea intelligent operation training system that AR and VR combines |
| CN107331272B (en) * | 2017-08-25 | 2019-07-02 | 福州盛世凌云环保科技有限公司 | Based on the medical teaching of emulation technology manikin application method and use system |
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| CN105825752A (en) * | 2016-04-22 | 2016-08-03 | 吉林大学 | Force feedback device-based virtual corneal surgery training system |
| CN107067856A (en) * | 2016-12-31 | 2017-08-18 | 歌尔科技有限公司 | A kind of medical simulation training system and method |
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