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Image detection method, training method of related model, related device and equipment

An image detection and detection model technology, applied in the field of artificial intelligence, can solve the problems of low accuracy, time-consuming and labor-intensive

Pending Publication Date: 2020-08-14
SHANGHAI SENSETIME INTELLIGENT TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the field of medical imaging, obtaining a large number of high-quality multi-organ annotations is very time-consuming and labor-intensive, and usually only experienced radiologists have the ability to annotate the data
Limited by this, the existing image detection models often have the problem of low accuracy when performing multi-organ detection

Method used

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  • Image detection method, training method of related model, related device and equipment
  • Image detection method, training method of related model, related device and equipment
  • Image detection method, training method of related model, related device and equipment

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Embodiment Construction

[0043] The solutions of the embodiments of the present application will be described in detail below in conjunction with the accompanying drawings.

[0044] In the following description, for purposes of illustration rather than limitation, specific details, such as specific system architectures, interfaces, and techniques, are set forth in order to provide a thorough understanding of the present application.

[0045] The terms "system" and "network" are often used interchangeably herein. The term "and / or" in this article is just an association relationship describing associated objects, which means that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist simultaneously, and there exists alone B these three situations. In addition, the character " / " in this article generally indicates that the contextual objects are an "or" relationship. In addition, "many" herein means two or more than two.

[0046] see figure 1 , figure 1 It ...

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Abstract

The invention discloses an image detection method, a training method of a related model, a related device and equipment, and the method comprises the steps: obtaining a sample medical image, wherein an actual region of at least one unlabeled organ of the sample medical image is pseudo labeled; detecting the sample medical image by using the original detection model to obtain a first detection result of a first prediction region comprising the unlabeled organ; detecting the sample medical image by using an image detection model to obtain a second detection result including a second prediction area of the unlabeled organ, wherein the network parameters of the image detection model are determined based on the network parameters of the original detection model; and adjusting the network parameters of the original detection model by using the difference between the first prediction area and the actual area and the difference between the first prediction area and the second prediction area.According to the scheme, the detection accuracy can be improved during multi-organ detection.

Description

technical field [0001] The present application relates to the technical field of artificial intelligence, in particular to an image detection method, a related model training method, and related devices and equipment. Background technique [0002] Medical images such as CT (Computed Tomography, computerized tomography) and MRI (Magnetic Resonance Imaging, nuclear magnetic resonance scanning) have important clinical significance. Among them, multi-organ detection is performed on medical images such as CT and MRI to determine the corresponding regions of each organ on the medical image, which has a wide range of applications in clinical practice, such as computer-aided diagnosis, radiotherapy planning, etc. Therefore, training an image detection model suitable for multi-organ detection has high application value. [0003] Currently, model training relies on large datasets with annotations. However, in the field of medical imaging, obtaining a large number of high-quality mul...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
CPCG06T7/0012G06T2207/10081G06T2207/10088G06T2207/20081G06T2207/20084G06T5/20
Inventor 黄锐胡志强张少霆李鸿升
Owner SHANGHAI SENSETIME INTELLIGENT TECH CO LTD
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