Multi-modal medical image segmentation method and terminal equipment
A medical image, multi-modal technology, applied in the field of image processing, can solve the problems of low accuracy of segmentation results and low efficiency of segmentation methods, and achieve the effects of improving segmentation efficiency, avoiding the influence of labeling results, and improving accuracy.
Active Publication Date: 2020-05-12
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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[0004] The embodiment of the present application provides a multi-modal medical image segmentation method and terminal equipment, which can solve the problems of low efficiency and low accuracy of segmentation results in existing multi-modal medical image segmentation methods
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[0059] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
[0060] It should be understood that when used in this specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude one or more other Presence or addition of features, wholes, steps, operations, elements, components and / or collections thereof.
[0061] In additi...
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The invention is suitable for the technical field of image processing, and provides a multi-mode medical image segmentation method and terminal equipment, and the method comprises the steps: obtaininga to-be-segmented data set which comprises medical images of multiple modes obtained through the photographing of a target part of the same photographing object; performing image segmentation on theto-be-segmented data set by using the trained segmentation model to obtain a segmentation result corresponding to the to-be-segmented data set, wherein the trained segmentation model is a segmentationmodel obtained after semi-supervised iterative training is carried out based on a training set, the training set comprises at least one group of marked data sets and multiple groups of unmarked datasets, and each group of data sets comprises medical images of multiple modes obtained by shooting a target part of the same shooting object. Through the method, the accuracy of a multi-modal medical image segmentation result is effectively improved while the multi-modal medical image segmentation efficiency is improved.
Description
technical field [0001] The present application belongs to the technical field of image processing, and in particular relates to a multimodal medical image segmentation method and terminal equipment. Background technique [0002] Multimodal medical image segmentation is an image processing technology that identifies the location of organs or lesions from multiple modal medical images (such as multimodal computer tomography images and multimodal magnetic resonance images, etc.). Being able to obtain information such as the shape and volume of the lesion is of great significance to the diagnosis, treatment and research of diseases. [0003] At present, the main method of multimodal medical image segmentation is to use deep convolutional neural network for image segmentation. In this method, a large amount of training data is used to train a deep convolutional neural network, and then the trained deep convolutional neural network is used for image segmentation. In the training...
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IPC IPC(8): G06T7/00G06T7/11G06T7/136
CPCG06T7/0012G06T7/11G06T7/136G06T2207/10072G06T2207/20081G06T2207/20084G06T2207/30004Y02T10/40
Inventor 闫凯李志成
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI