Intelligent detection and early warning method and system for outer envelope in prostate operation

An intelligent detection and early warning system technology, applied in character and pattern recognition, instruments, computer parts, etc., to achieve the effect of enriching the original data set and good detection effect

Pending Publication Date: 2019-05-14
WUHAN TANGJI TECH
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Problems solved by technology

[0005] Aiming at the specific needs of early warning analysis and application of minimally invasive plasma bipolar resection surgery and the development status of medical image processing technology, the present invention proposes a method and system for intelligent detection and early warning of the outer capsule in prostate surgery, focusi

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  • Intelligent detection and early warning method and system for outer envelope in prostate operation
  • Intelligent detection and early warning method and system for outer envelope in prostate operation
  • Intelligent detection and early warning method and system for outer envelope in prostate operation

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Embodiment Construction

[0035] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments, but the embodiments should not be understood as limiting the present invention.

[0036] The present invention mainly performs real-time early warning and recognition for the outer envelope image in the video image of minimally invasive prostate surgery. Such as figure 1 As shown, the early warning system mainly includes an image acquisition module, an image processing module, and an image detection and early warning module.

[0037] The image acquisition module is used to collect and store image information and models. It contains a switch interface connected to the digital video interface DVI of the endoscope image device, an image data memory, and an image model memory; the switch interface is responsible for connecting the endoscope The 1920×1200p / 60Hz CVT-RB video stream output by the digital video interface is converted into 1920×1080p / 60Hz RGB...

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Abstract

The invention discloses an intelligent detection and early warning method and system for an outer envelope in a prostate operation. The method comprises the following steps: 1) acquiring outer envelope image data in a prostate operation video; 2) carrying out gray processing and singular value decomposition on the outer envelope data, and extracting a principal component characteristic value of the image; 3) performing image enhancement on the outer coating image after the image preprocessing in the first step by adopting a deep bilateral learning method; 4) neural network training; 5) detection and early warning. According to the invention, the latest artificial intelligence image recognition technology is utilized to carry out target detection on the prostate envelope, so that an intelligent early warning function is provided for the operations. Different from the existing static medical image recognition technology, the method is characterized in that dynamic images of an operationsite video need to be recognized, early-warned and analyzed. By means of image preprocessing measures such as data expansion, principal component analysis and image enhancement, speed and precision are balanced, and the actual application requirements of prostate operation auxiliary early warning are met.

Description

Technical field [0001] The present invention relates to the technical field of artificial intelligence target detection, in particular to a method and system for intelligent detection and early warning of outer membrane in prostate surgery. Background technique [0002] In the field of traditional image processing, target detection is a very popular key technology, and more researches include face detection and pedestrian detection. Traditional target detection generally uses a sliding window framework, which mainly includes three steps: one is to use the sliding window to select candidate regions; the other is to extract visual features related to the candidate regions; the third is to use classifiers for recognition. The more classic algorithm is a multi-scale deformable component model. This algorithm can be regarded as an extension of the "gradient histogram + support vector machine" method. The disadvantage is that it is more complex, slow in operation, and cannot support ap...

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Application Information

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IPC IPC(8): G06K9/62G06K9/36
CPCG06V10/20G06F18/00
Inventor 郭成城王行环毋世晓赵亚楠郝玉洁
Owner WUHAN TANGJI TECH
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