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Image segmentation method and system

An image segmentation and image technology, applied in the field of deep learning, can solve the problems of unclear distribution of surrounding tissues, unclear intermediate contours, blurred images of kidneys, etc., and achieve the effect of improving blur, low cost, and ability to improve

Pending Publication Date: 2021-09-17
BEIJING UNIV OF TECH
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Problems solved by technology

Existing methods for segmenting renal ultrasound images based on deep learning have problems dealing with blurred kidney images, unclear middle contours, unclear distribution with surrounding tissues, and weird shapes, etc.

Method used

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  • Image segmentation method and system

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Embodiment Construction

[0052] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0053] In order to facilitate the subsequent detailed description of the present invention, some technical terms are described:

[0054] Attention Mechanism: The attention mechanism mimics the way humans look at objects: by taking a simple glance, analyzing the important part of the image, and then focusing on that location, rather than giving equ...

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Abstract

The invention provides an image segmentation method and system, and the method comprises the steps: inputting a to-be-segmented image into an image segmentation model, and obtaining a segmented target image outputted by the image segmentation model, wherein the image segmentation model is obtained by training a sample image set; and enabling the image segmentation model to be used for determining a target feature map corresponding to the to-be-segmented image based on an attention mechanism and a residual network, and determining a segmented target image based on the target feature map and a pyramid scene analysis network. Important features in the to-be-segmented image can be effectively concerned, unnecessary features are suppressed, the segmented image is prevented from being blurred, and the segmentation precision of image segmentation is improved.

Description

technical field [0001] The present invention relates to the technical field of deep learning, in particular to an image segmentation method and system. Background technique [0002] Hydronephrosis is a common kidney disease that can lead to a series of complications such as abdominal mass, hematuria, uremia, high blood pressure and even kidney rupture. B-mode ultrasonography is a basic examination for patients with suspected hydronephrosis, which is convenient, time-saving, economical and radiation-free. B-mode ultrasound imaging uses ultrasound beams to scan the human body to obtain two-dimensional cross-sectional tomographic images reflecting human tissues and organs. [0003] The combination of medical imaging and artificial intelligence has become popular in recent years. Artificial intelligence medical imaging technology has largely alleviated the shortage of medical resources and the imbalance between different regions, and promoted doctors' diagnostic capabilities. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/11G06N3/04G06N3/08G16H30/20
CPCG06T7/11G06N3/084G16H30/20G06T2207/10132G06T2207/20081G06T2207/30084G06N3/045
Inventor 李建强文棚嶒徐春
Owner BEIJING UNIV OF TECH
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