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Medical image segmentation network model training method, segmentation method and related equipment

A technology for medical images and network models, applied in biological neural network models, image analysis, neural learning methods, etc., can solve the problems of low liver labeling efficiency, increase the time cost and labor cost of liver labeling, etc., to improve segmentation efficiency, increase Accurate effect of training data set and segmentation labels

Pending Publication Date: 2020-12-15
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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Problems solved by technology

[0003] In the existing technology, doctors and experts with professional knowledge and clinical experience mainly label abdominal CT at the voxel level to obtain part of the label outline of the liver, so as to formulate the patient's surgical plan, but this method increases the liver label production. Time cost and labor cost, and the efficiency of liver labeling is low

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  • Medical image segmentation network model training method, segmentation method and related equipment
  • Medical image segmentation network model training method, segmentation method and related equipment
  • Medical image segmentation network model training method, segmentation method and related equipment

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Embodiment Construction

[0031] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

[0032] This application proposes a training method for medical image segmentation network model, please refer to figure 1 , figure 1 It is a schematic flowchart of an embodiment of the training method of the medical image segmentation network model provided by the present application. The training method of the medical image segmentation network model in this embodiment can be applied to medical image segmentation equipment, and can also be appli...

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Abstract

The invention provides a medical image segmentation network model training method, a segmentation method and related equipment. The network model training method comprises the following steps: training a segmentation network model by using a first medical image and a first segmentation label of the first medical image to obtain a segmentation network model; inputting the second medical image intothe segmentation network model to obtain a second segmentation label; and obtaining a modified second segmentation label, and training the segmentation network model by using the first medical image,the first segmentation label of the first medical image, the second medical image and the modified second segmentation label. According to the invention, the medical image segmentation efficiency is improved.

Description

technical field [0001] The present application relates to the technical field of medical image segmentation, in particular to a training method of a medical image segmentation network model, a segmentation method and related equipment. Background technique [0002] The liver is the largest gland in the human body. Its functions are very complex and important. It has the functions of participating in metabolism, bile secretion, phagocytosis defense, and detoxification. Due to the particularity and importance of the liver, liver lesions are often fatal. At present, the main treatment methods for liver cancer include surgery, interventional therapy, and radiation therapy. Among them, liver resection and liver transplantation are still the most effective radical cure methods. When performing liver surgery, doctors need to carefully monitor the inside of the liver and the lesion. Precise surgical planning can only be made with comprehensive control, so accurate segmentation of th...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/11G06N3/08G06N3/02
CPCG06T7/0012G06T7/11G06N3/08G06N3/02G06T2207/10081G06T2207/20084G06T2207/20081G06T2207/30056
Inventor 贾富仓宋宠宠贺宝春
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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