Training method and device for blood vessel segmentation model, application method and device

A technology of segmentation model and training method, applied in the field of deep learning, can solve problems such as imbalance of blood vessel categories, and achieve the effect of improving training effect and segmentation effect

Active Publication Date: 2022-02-08
INFERVISION MEDICAL TECH CO LTD
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  • Claims
  • Application Information

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Problems solved by technology

[0005] In view of this, the embodiment of the present application provides a training method and device for a blood vessel segmentation model, an application method and a device, which can solve the problem of unbalanced types of blood vessels in different parts, and improve the training effect and segmentation effect

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  • Training method and device for blood vessel segmentation model, application method and device
  • Training method and device for blood vessel segmentation model, application method and device
  • Training method and device for blood vessel segmentation model, application method and device

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Embodiment Construction

[0034] The following will clearly and completely describe the technical solutions in the embodiments of the application with reference to the drawings in the embodiments of the application. Apparently, the described embodiments are only some, not all, embodiments of the application. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

[0035] Application overview

[0036] CT (Computed Tomography), that is, electronic computer tomography, it uses precisely collimated X-ray beams, γ-rays, ultrasound, etc., together with highly sensitive detectors, to conduct cross-sectional scans one after another around a certain part of the human body. It has the characteristics of fast scanning time and clear images, and can be used for the examination of various diseases.

[0037] Deep learning implements artificial intelligence in computi...

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Abstract

The present application provides a method and device for training a blood vessel segmentation model, and an application method and device. The training method of the blood vessel segmentation model includes: extracting the blood vessel midline in the blood vessel sample image; determining the loss weight of each pixel point according to the distance between each pixel point in the blood vessel sample image and the blood vessel midline; The weight, the blood vessel segmentation label corresponding to the blood vessel sample image, and the blood vessel segmentation result output by the blood vessel segmentation model, determine the first loss function value; the blood vessel segmentation model is trained according to the first loss function value, which can solve the category imbalance of different parts of the blood vessels. problem, improve the training effect and segmentation effect.

Description

technical field [0001] The present application relates to the technical field of deep learning, in particular to a training method and device for a blood vessel segmentation model, and an application method and device. Background technique [0002] In recent years, scholars have used deep learning technology to diagnose and analyze diseases. It has become a trend to apply deep learning to improve disease diagnosis and auxiliary treatment in the medical field, and it has great research significance in medical image segmentation. [0003] However, the accuracy of the current blood vessel segmentation algorithm needs to be improved. There will be some defects in the blood vessel segmentation results obtained by the blood vessel segmentation model. The number of classes in the mediastinum part and intrapulmonary vessel part in the vessel segmentation label (Ground Truth, GT) of . [0004] Usually, the industry will use focal loss function (focalloss) or difficult sample mining ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/11G06T7/00G06N3/04G06N3/08
CPCG06T7/11G06T7/0012G06N3/08G06T2207/10081G06T2207/20081G06T2207/20084G06T2207/30101G06T2207/10088G06N3/045
Inventor 刘恩佑张欢王瑜王少康陈宽
Owner INFERVISION MEDICAL TECH CO LTD
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