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Pituitary tumor image classification method, pituitary tumor image classification system and electronic equipment

A pituitary tumor and imaging technology, applied in the field of image processing, can solve the problems of low classification accuracy, interference of doctors' cognitive ability and subjective factors, etc.

Active Publication Date: 2021-01-08
SUN YAT SEN UNIV CANCER CENT
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  • Description
  • Claims
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Problems solved by technology

The classification of pituitary tumors generally relies on experienced doctors for manual interpretation, which is easily interfered by doctors' cognitive ability and subjective factors, and the classification accuracy is low

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  • Pituitary tumor image classification method, pituitary tumor image classification system and electronic equipment
  • Pituitary tumor image classification method, pituitary tumor image classification system and electronic equipment
  • Pituitary tumor image classification method, pituitary tumor image classification system and electronic equipment

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Embodiment Construction

[0031] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0032] It should be noted that the terms "comprising" and "having" and any variations thereof in the embodiments of the present application and the drawings are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but optionally also includes unlisted steps or units, or optionally further includes For other steps or...

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Abstract

The embodiments of the application discloses a pituitary tumor image classification method, a pituitary tumor image classification system and electronic equipment. The method comprises the following steps: acquiring a magnetic resonance image of a brain to be classified; inputting the magnetic resonance image of the brain to be classified into a classification model, wherein the classification model is an artificial neural network comprising an attention module, and the classification model is obtained after training by taking the extracted magnetic resonance images form the area where the pituitary tumor is located as a first training sample; extracting image features in the magnetic resonance image of the brain through the classification model, determining the importance degree of each image feature in the the magnetic resonance image of the brain through the attention module, and obtaining a classification result corresponding to the magnetic resonance image of the brain based on the importance degree of each image feature. By implementing the embodiment of the invention, the importance degree of the image feature can be determined through the attention module according to the contribution of each image feature to the classification task, so that the classification accuracy is improved.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a pituitary tumor image classification method, system and electronic equipment. Background technique [0002] Pituitary tumors are common primary tumors in the nervous system, accounting for 10%-25% of all primary brain tumors, second only to gliomas and meningiomas. The diagnosis of pituitary tumors is mainly based on MRI-enhanced scans and pituitary hormone examinations, which requires doctors with rich clinical experience to make a preliminary diagnosis. Thereby there are following deficiencies: the pituitary tumor incidence rate is high, and classification is various. The classification of pituitary tumors generally relies on experienced doctors for manual interpretation, which is easily interfered by doctors' cognitive ability and subjective factors, and the classification accuracy is low. Therefore, how to improve the classification accuracy of pituitary tumors h...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/055A61B5/00
CPCA61B5/055A61B5/7264A61B5/7267A61B2576/026
Inventor 任间蒋小兵李弘于赵齐
Owner SUN YAT SEN UNIV CANCER CENT
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