Enteroscope image polyp error detection inhibition device based on deep learning

A suppression device and deep learning technology, applied in the intersection of computer science and medicine, can solve problems such as false detection, and achieve the effect of reducing the number and good versatility

Active Publication Date: 2021-04-16
杭州优视泰信息技术有限公司
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Problems solved by technology

The second is that when the endoscope lens is dirty or the object is too close, there may be image frame...

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  • Enteroscope image polyp error detection inhibition device based on deep learning
  • Enteroscope image polyp error detection inhibition device based on deep learning
  • Enteroscope image polyp error detection inhibition device based on deep learning

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Embodiment Construction

[0041] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, and do not limit the protection scope of the present invention.

[0042] The embodiment provides a device for suppressing false polyp detection in colonoscopy images based on deep learning, which includes a computer memory, a computer processor, and a computer program stored in the computer memory and executable on the computer processor. The computer memory includes a feature extraction module, a detection head module, an invalid frame discrimination module, and a colonoscopy image polyp false detection suppression model of a suppression processing module, and the colonoscopy image polyp false detection suppression model is used to sup...

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Abstract

The invention discloses an enteroscope image polyp error detection inhibition device based on deep learning. The device comprises the following steps: obtaining a to-be-detected enteroscope image, and inputting the to-be-detected enteroscope image into an enteroscope image polyp error detection inhibition model; after the feature extraction module is used for extracting a feature map of the enteroscope image to be detected, adopting the detection head module for detecting the feature map, calculating and outputting a detection result, and the invalid frame discrimination module is used for carrying out invalid frame discrimination on the feature map and outputting a discrimination result; performing suppression output by the suppression processing module according to the detection result and the judgment result, suppressing the output of all detection boxes in the detection result when the enteroscope image to be detected is classified as an invalid frame according to the judgment result, and otherwise, outputting the detection boxes and confidence after the detection result is normally screened according to a confidence threshold. Under the condition that the recall rate and the running speed of the detection method are hardly influenced, the number of false detection frames is reduced, so that the detection efficiency is improved, and the practicability of the detection method is improved.

Description

technical field [0001] The invention belongs to the intersecting field of computer science and medicine, and in particular relates to a device for suppressing false detection of polyps in colonoscopy images based on deep learning. Background technique [0002] Colorectal polyps are abnormal masses raised on the surface of the colorectum, which have a certain risk of malignant transformation leading to colorectal cancer. At present, the most widely used and effective diagnostic method is to examine the intestinal tract with an endoscope. Modern endoscopes generally use a camera to replace the previous optical structure. By collecting images and then transmitting them to the computer for display, doctors can find polyps and other lesions by examining the endoscope images to determine the patient's condition. [0003] In the current endoscopic examination process, the doctor mainly relies on the naked eye to observe the endoscopic image to detect polyps. The detection rate is...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06K9/62G06N3/04G06N3/08
Inventor 顾梦奇史勇强
Owner 杭州优视泰信息技术有限公司
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