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Method and system for medical image automatic segmentation, apparatus and storage medium

A medical image and automatic segmentation technology, applied in the application field of computer analysis technology, can solve the problems of increasing segmentation difficulty, lack of universality and robustness, and influence of image data, reducing information processing capacity, improving classification performance, The effect of accurate segmentation

Active Publication Date: 2018-11-27
SOUTH CENTRAL UNIVERSITY FOR NATIONALITIES
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

With the substantial improvement of temporal and spatial resolution of imaging equipment, massive image data greatly increases the difficulty of segmentation
In addition, for complex medical images (such as heart images), existing segmentation methods are easily affected by image quality, lack of universality and robustness

Method used

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  • Method and system for medical image automatic segmentation, apparatus and storage medium
  • Method and system for medical image automatic segmentation, apparatus and storage medium
  • Method and system for medical image automatic segmentation, apparatus and storage medium

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Embodiment 1

[0049] figure 1 It is a schematic flow chart of the automatic segmentation method for medical images provided in Embodiment 1 of the present invention. The execution subject of the automatic segmentation method provided in the embodiment of the present invention may be the automatic segmentation system provided in the embodiment of the present invention, and the system can be integrated into a mobile terminal Devices (for example, smart phones, tablet computers, notebooks, etc.) can also be integrated into the server, and the automatic segmentation system can be implemented by hardware or software. The automatic segmentation method provided by the embodiment of the present invention is particularly suitable for the situation of computer-aided diagnosis of cardiac images based on nuclear magnetic images, which will be described below in conjunction with the embodiments.

[0050] Such as figure 1 As shown, the automatic segmentation method specifically includes:

[0051] S101,...

Embodiment 2

[0062] figure 2 It is a schematic structural diagram of the automatic segmentation system of medical images provided by Embodiment 2 of the present invention. The system can be integrated into mobile terminal equipment (such as smart phones, tablet computers, notebooks, etc.), and can also be integrated into servers. The positioning device can Implemented in hardware or software.

[0063] Such as figure 2 As shown, the system specifically includes a saliency map generation module 201, a training module 202, an initial segmentation module 203, a contour construction and optimization module 204, and a contour generation module 205;

[0064] The saliency map generation module 201 adopts the visual attention model to obtain the saliency map of the medical image to be trained;

[0065] The training module 202 is used to input the saliency map of the medical image to be trained into the deep learning neural network, so as to train the parameters of the deep learning neural netwo...

Embodiment 3

[0151] Figure 11 It is a schematic structural diagram of the device provided in Embodiment 3 of the present invention, and the device can be used to realize the automatic segmentation method of medical images according to the embodiment of the present invention.

[0152] exist Figure 11 Among them, a central processing unit (CPU) 601 executes various processes according to programs stored in a read only memory (ROM) 602 or programs loaded from a storage section 608 to a random access memory (RAM) 603 . In the RAM 603, data required when the CPU 601 executes various processes and the like is also stored as necessary. The CPU 601 , ROM 602 , and RAM 603 are connected to each other via a bus 604 . The input / output interface 605 is also connected to the bus 604 .

[0153] The following components are also connected to the input / output interface 605: an input section 606 (including a keyboard, a mouse, etc.), an output section 607 (including a display such as a cathode ray tub...

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Abstract

The present invention provides a method and a system for medical image automatic segmentation. The method for medical image automatic segmentation comprises: obtaining a salient image of a to-be-trained medical image by using a visual attention model, and using the salient image to train parameters of a deep learning neural network; obtaining a salient image of a to-be-segmented medical image by the visual attention model, and inputting the to-be-segmented medical image to the trained deep learning neural network for segmentation, to obtain an initial segmentation result; using the initial segmentation result to construct an initial contour of a statistical shape model and to optimize the statistical shape model, and using the optimized statistical shape model to segment the to-be-segmented medical image. The method combines the statistical shape model and the deep learning model, and calculated amount of matching operation in the statistical shape model is reduced by using the initialsegmentation result of the deep learning network, thereby realizing fast and accurate segmentation of the three-dimensional medical image by the statistical shape model.

Description

technical field [0001] The invention belongs to the application field of computer analysis technology of medical images, and in particular relates to an automatic segmentation method and system of medical images. Background technique [0002] In recent years, with the continuous development of medical diagnosis and imaging technology, various computer-aided analysis methods of medical images have been widely used in predicting diseases and guiding interventional treatment. The heart is the most important organ of the human body, which is responsible for running blood to all parts of the body. Heart disease directly affects people's life and death. According to statistics, heart disease is one of the diseases with the highest mortality rate in the world, which has a huge impact on social and economic development. For this reason, it has very important social significance and use value to carry out new technology research on early diagnosis and treatment of heart disease. ...

Claims

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Application Information

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IPC IPC(8): G06T7/12G06T7/00
CPCG06T7/0012G06T2207/10072G06T2207/20081G06T2207/20084G06T2207/30048G06T7/12
Inventor 胡怀飞刘海华潘宁李旭高智勇
Owner SOUTH CENTRAL UNIVERSITY FOR NATIONALITIES
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