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Early gastric cancer endoscope real-time auxiliary detection system based on target detection algorithm

A target detection algorithm and early gastric cancer technology, applied in gastroscopy, endoscopy, computing, etc., to achieve good clinical results, high objectivity and consistency, and improve the effect of early detection rate

Pending Publication Date: 2022-04-12
NANJING DRUM TOWER HOSPITAL +1
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Problems solved by technology

However, these technologies are all passive applications at present. How to use these technologies and when to allow these assistive technologies to intervene in endoscopic observation also depends on the doctor's operating experience and awareness.

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  • Early gastric cancer endoscope real-time auxiliary detection system based on target detection algorithm

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Embodiment Construction

[0019] The above-mentioned content of the present invention will be described in further detail below by the form of the embodiment, but this should not be interpreted as the scope of the above-mentioned theme of the present invention being limited to the following embodiments, all technologies realized based on the above-mentioned content of the present invention belong to scope of the invention.

[0020] The invention provides a real-time auxiliary detection system for early gastric cancer endoscopy based on a target detection algorithm, and establishes a Yolo detection model based on Darknet53. The modeling information comes from the computer-recognizable annotations obtained by annotating images of early gastric mucosal tumor lesions information, the endoscopic real-time auxiliary detection system for early gastric cancer includes a model prediction module, an image acquisition module and a real-time recognition module.

[0021] Among them, the model prediction module is a...

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Abstract

The invention relates to an early gastric cancer endoscope real-time auxiliary detection system based on a target detection algorithm, which is characterized in that a Darknet53-based Yolo detection model is established, and modeling information is derived from computer-recognizable labeling information obtained by labeling an early neoplastic lesion image of gastric mucosa; the early gastric cancer endoscope real-time auxiliary detection system comprises a model prediction module, an image acquisition module and a real-time identification module. According to the endoscope auxiliary diagnosis system with the high sensitivity prompting capacity under common light source or electronic dyeing light source endoscope examination, the deep learning technology is applied to an early gastric cancer endoscope real-time auxiliary detection system, and the early detection rate of major diseases of the digestive tract can be increased by using the system.

Description

technical field [0001] The invention relates to the technical fields of digestive endoscopy and computer vision processing, in particular to an endoscopic real-time auxiliary detection system for early gastric cancer based on a target detection algorithm. Background technique [0002] Lesion detection is the basis of early gastric cancer diagnosis, and its core is to find all suspicious lesions as much as possible to ensure that no missed diagnosis occurs. Gastroscopy combined with biopsy pathological examination (hereinafter referred to as gastroscopy) is currently the most important method for detecting early gastric cancer. Due to the different knowledge levels and operating experience of different endoscopists, the quality of endoscopists' examinations varies greatly, and inexperienced endoscopists often make missed diagnoses. Previous Meta-analysis showed that the missed diagnosis rate of gastric cancer during gastroscopy can be as high as 10%. [0003] In order to im...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06V10/25A61B1/273A61B1/04
Inventor 邹晓平徐桂芳王雷胡延兴唐德华
Owner NANJING DRUM TOWER HOSPITAL
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