Micropapilla detection system based on YOLOv5

A detection system and nipple technology, applied in image data processing, image enhancement, instruments, etc., can solve the problems of low accuracy, slow recognition of micro-nipples, and low efficiency by human eyes, so as to enhance the detection ability, improve the detection effect, The effect of small receptive fields

Active Publication Date: 2021-09-03
SHANDONG NORMAL UNIV
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Problems solved by technology

Therefore, an automatic and accurate micropapillary detection system is particularly important to assist doctors to quickly and accurately identify the micropapillary structure, avoiding the slow speed, low efficiency, and low accuracy of human eyes to identify micropapillary

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  • Micropapilla detection system based on YOLOv5
  • Micropapilla detection system based on YOLOv5
  • Micropapilla detection system based on YOLOv5

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Embodiment Construction

[0031] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0032] It should be noted that the following detailed description is exemplary and intended to provide further explanation of the present invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0033] It should be noted that the terminology used here is only for describing specific embodiments, and is not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinations thereof.

[0034] Th...

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Abstract

The invention provides a micropapilla detection system based on YOLOv5. The micropapilla detection system comprises a lung adenocarcinoma pathological image acquisition module, a detection model training module and a micropapilla detection module; a feature extraction module in the detection model training module adds a layer of feature extraction on the basis of a BottleneckCSP network structure to obtain a shallow feature map, so that the multiple of downsampling of the feature extraction module is reduced by half; the feature fusion module is used for down-sampling the shallow feature map and splicing the shallow feature map with the deep feature map, so that the features of the shallow feature map and the deep feature map are fused, and the small target detection capability of the network is enhanced; and the prediction module replaces the GIoU loss with the CIoU loss, optimizes the prediction frame, improves the regression speed and precision of the prediction frame, and is more suitable for the detection of micronipples.

Description

technical field [0001] The invention belongs to the field of pathological image processing, and in particular relates to a micropapillary detection system based on YOLOv5. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] According to statistics from the American Cancer Society, more than 150,000 patients die of lung cancer every year, which is one of the most widespread cancers in the world, and its overall incidence is on the rise worldwide. According to histological characteristics and cell type and response to traditional treatment, lung cancer can be divided into two main types, non-small cell lung cancer and small cell lung cancer, of which non-small cell lung cancer accounts for about 80% of lung cancer. [0004] Lung adenocarcinoma is one of the common types of non-small cell lung cancer. It originates from the glandular epithelium ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/136G06K9/32G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06T7/0012G06T7/136G06N3/08G06T2207/20081G06T2207/20084G06T2207/20104G06T2207/30068G06N3/045G06F18/253G06F18/214
Inventor 郑元杰高远丁艳辉姜岩芸隋晓丹
Owner SHANDONG NORMAL UNIV
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