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Image processing device, electronic apparatus, and medium

An image processing device and image technology, applied in the field of computer vision, can solve problems such as difficult to learn features, small number, and complexity

Pending Publication Date: 2022-08-05
北京医准智能科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the amount of medical image data is relatively small compared with natural images, and the problems to be solved are more complex, so it is difficult to learn the most suitable features in this way

Method used

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  • Image processing device, electronic apparatus, and medium
  • Image processing device, electronic apparatus, and medium
  • Image processing device, electronic apparatus, and medium

Examples

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Embodiment Construction

[0022] Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. Also, for the sake of clarity, parts unrelated to describing the exemplary embodiments are omitted from the drawings.

[0023] In the present disclosure, it should be understood that terms such as "comprising" or "having" are intended to indicate the presence of features, numbers, steps, acts, components, parts, or combinations thereof disclosed in this specification, and are not intended to exclude a or multiple other features, numbers, steps, acts, components, parts, or combinations thereof may exist or be added.

[0024] In addition, it should be noted that the embodiments of the present disclosure and the features of the embodiments may be combined with each other under the condition of no conflict. The present disclosure will be described in detail below with reference to th...

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PUM

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Abstract

The embodiment of the invention provides an image processing device, electronic equipment and a medium. The image processing device comprises an input layer, a residual network, a feature fusion layer, a lump feature extraction network and a calcification feature extraction network. Wherein the input layer is used for obtaining a first image of the same mammary gland lesion area at a first body position and a second image of the same mammary gland lesion area at a second body position. The residual network is used for processing the first image and the second image respectively to obtain a first feature of the first image and a second feature of the second image. And the feature fusion layer is used for fusing the first feature and the second feature to obtain a fused feature. A lump feature extraction network is used to process the fused feature to determine a lump feature and a first probability of malignancy. A calcification feature extraction network is used to process the fused feature to determine a calcification feature and a second probability of malignancy.

Description

technical field [0001] The present specification relates to the technical field of computer vision, and in particular, to an image processing apparatus, electronic equipment and medium. Background technique [0002] In the field of medical imaging, medical images from patients are often displayed. Mammograms or breast tomograms can provide images of a patient's breasts. Several methods already exist in the related art for detecting and alerting the user to a region of interest within a sequence of medical images. With the development of deep learning, the use of network to extract image features has become the mainstream method in medical imaging problems. However, the data of medical images is relatively small compared with natural images, and the problems to be solved are more complex, so it is difficult to learn the most suitable features in this way. SUMMARY OF THE INVENTION [0003] To solve the problems in the related art, the embodiments of the present disclosure...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06K9/62G06V10/80G06V10/764
CPCG06T7/0012G06T2207/10116G06T2207/20081G06T2207/30068G06F18/2415G06F18/253
Inventor 张可欣王雅倩王子腾丁佳吕晨翀
Owner 北京医准智能科技有限公司