Medical image segmentation method, device and equipment and readable storage medium

A medical image and image segmentation technology, applied in the field of medical image processing, can solve the problems of high requirement of medical image detail, loss of medical image segmentation, affecting quantitative calculation of cardiac ejection volume, etc.
CN110689548AActive Publication Date: 2020-01-14LANGCHAO ELECTRONIC INFORMATION IND CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
LANGCHAO ELECTRONIC INFORMATION IND CO LTD
Publication Date
2020-01-14

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Abstract

The invention discloses a medical image segmentation method, device and equipment and a readable storage medium. The method comprises the steps: obtaining a to-be-segmented medical image, and inputting the medical image into a deep learning image segmentation network; carrying out tissue segmentation on the medical image by utilizing the target segmentation parameter which focuses on the specifiedtissue edge to obtain an image segmentation result; the training process of the deep learning image segmentation network comprises the following steps: determining an edge enhancement region of a medical image training sample by utilizing a segmentation label corresponding to the medical image training sample; inputting the medical image training sample into a deep learning image segmentation network for tissue segmentation to obtain a training segmentation result; when a loss function is used to calculate a loss value, increasing a loss weight for a pixel corresponding to an edge enhancementregion in the training segmentation result; and adjusting the segmentation parameter of the deep learning image segmentation network by using the loss value to obtain a target segmentation parameter.The method can improve the medical image segmentation precision.
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Description

Technical field

[0001] The present invention relates to the technical field of medical image processing, in particular to a medical image segmentation method, device, equipment and readable storage medium. Background technique

[0002] Medical image segmentation is of great use in imaging diagnosis. Automatic segmentation of medical images can help doctors confirm the size of diseased tumors and quantitatively evaluate the effects before and after treatment. In addition, the boundary recognition and screening of organs and lesions is also a routine work of imaging doctors. Both CT and MRI data are three-dimensional data, which means that the segmentation of organs and lesions needs to be performed layer by layer. If it is divided manually, it will bring heavy workload to the doctor.

[0003] At present, many scholars have proposed many segmentation methods for medical images. However, due to the complexity of medical images and the changeable segmentation targets, there are stil...

Claims

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