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A hepatic echinococcosis lesion segmentation method and system based on a neural network

A neural network and convolutional neural network technology, applied in the field of liver echinococcosis detection, can solve problems such as poor results, reduce missed diagnosis, improve diagnostic efficiency and accuracy

Active Publication Date: 2019-04-26
TSINGHUA UNIV
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Problems solved by technology

Patients with alveolar echinococcosis do not respond well to oral medication, and must undergo surgical resection to achieve a radical cure

Method used

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  • A hepatic echinococcosis lesion segmentation method and system based on a neural network
  • A hepatic echinococcosis lesion segmentation method and system based on a neural network
  • A hepatic echinococcosis lesion segmentation method and system based on a neural network

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Embodiment Construction

[0050] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0051] Such as figure 1 As shown, a neural network-based segmentation method for liver hydatid lesions, including:

[0052] S1. Obtain the segmented liver region from the cystic hydatid CT image set through the liver segmentation model, train and verify the cystic hydatid lesion segmentation model based on the liver segmentation results, and mark whether the lesion is active during training and verification;

[0053] S2. Obtain the segmented liver region from the CT image set of alveolar echinococcosis through the liver segmentation model, identify and segment the blood vessels of the acquired liver region, train and verify the segmentation of alveolar echinococcosis lesion based on the results of blood vessel segmentation and liver segmentation Model, during training and verification, mark whether the lesion invades blood vessels an...

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Abstract

The invention discloses a hepatic echinococcosis focus segmentation method and a hepatic echinococcosis focus segmentation system based on a neural network. The method comprises the following steps: S1, training and verifying a cystic echinococcosis focus segmentation model; S2, training and verifying a follicular echinococcosis focus segmentation model; S3, obtaining a segmented liver region fromthe one-pack worm CT image, and inputting the liver region into the focus recognition model to obtain a recognition result; S4, when it is determined that the recognition result is the cystic echinococcosis focus, inputting the VOI region into the cystic echinococcosis focus segmentation model to obtain a first segmentation result; And S5, when it is determined that the recognition result is thefollicular echinococcosis lesion, performing blood vessel recognition and segmentation on the VOI region, and inputting the blood vessel segmentation result and the VOI region into the follicular echinococcosis lesion segmentation model to obtain a second segmentation result. According to the method and the system provided by the invention, fusion recognition and feature extraction are carried outon the multi-modal medical image through various models, a doctor is assisted to carry out echinococcosis screening work, and the diagnosis efficiency and accuracy are improved.

Description

technical field [0001] The invention relates to the technical field of liver echinococcosis detection, in particular to a method and system for segmenting hepatic echinococcosis lesions based on a neural network. Background technique [0002] Hydatid disease is a serious zoonotic parasitic disease that spreads across all continents of the world. The number of people and patients threatened by echinococcosis in my country ranks first in the world, and the infection rate of hermaphrodite echinococcosis in the hardest-hit Sanjiangyuan area of ​​Qinghai Province is 8.93-12.38%. The environment in this area is harsh, medical resources are scarce, and the level of doctors is not homogeneous. Echinococcosis is mainly divided into cystic echinococcosis and alveolar echinococcosis. The impact of cystic echinococcosis on the host is mainly manifested in the damage to the structure and function of parasitic tissues and organs. During its expansive growth, it produces compression sympt...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/11G06T7/136G06N3/04G06T5/30A61B6/00A61B6/03
CPCG06T5/30G06T7/11G06T7/136A61B6/032A61B6/5205A61B6/5211G06T2207/20081G06T2207/20084G06T2207/10081G06T2207/30101G06T2207/30056G06N3/045
Inventor 王展沈新科胥瑾辛盛海樊海宁王海久周瀛任利阳丹才让马洁王志鑫
Owner TSINGHUA UNIV
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