A Fully Automatic 3D Liver Segmentation Method Based on Convolutional Neural Networks

A convolutional neural network, fully automatic technology, used in image analysis, image data processing, instruments, etc., can solve the problems of long segmentation time, low contrast and weak boundaries, over-segmentation, etc., to avoid under-segmentation and over-segmentation, accurate The effect of liver segmentation results
CN104992430BActive Publication Date: 2017-12-22ZHEJIANG DE IMAGE SOLUTIONS CO LTD
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Patents(China)
Current Assignee / Owner
ZHEJIANG DE IMAGE SOLUTIONS CO LTD
Publication Date
2017-12-22

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Abstract

The invention relates to the field of medical image processing and aims to provide a fully-automatic three-dimensional liver segmentation method based on a convolution nerve network. The fully-automatic three-dimensional liver segmentation method based on the convolution nerve network comprises the following processes: preparing a training set, and training the convolution nerve network, processing CTA volume data of an abdominal liver by utilizing the trained convolution nerve network to obtain a segmentation result of the liver. The liver is segmented by means of the three-dimensional convolution nerve network; the three-dimensional liver segmentation method is fully automatic and can also prevent under-segmentation and over-segmentation phenomena well; and the accurate liver segmentation result is obtained.
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Description

technical field

[0001] The invention relates to the field of medical image processing, in particular to a fully automatic three-dimensional liver segmentation method based on a convolutional neural network. Background technique

[0002] At present, liver disease is a disease with a relatively high incidence rate clinically, which directly threatens people's lives, so the accurate diagnosis of liver disease has important medical significance. Clinically, doctors often use a CT machine, that is, a computerized tomography machine, to obtain a series of planar grayscale tomographic images of the liver, and to judge the lesion location, characteristics, size, and surrounding tissue of the lesion by continuously viewing these images. relationship between etc. The extraction and quantitative analysis of the liver play a key role in accurately diagnosing liver diseases and formulating appropriate surgical plans. Clinically, the extraction of the liver is often outlined directly on...

Claims

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