Artificial intelligence-based quick grading identification method and system for burn and scald images

A technology of artificial intelligence and recognition system, which is applied in the field of image processing of medical burn and scald wounds, can solve problems such as the prognosis grading and prediction of burn and scald wound images and photos that have not yet been seen with artificial intelligence image recognition technology, and achieve artificial intelligence recognition, convenient operation, The effect of improving accuracy

Pending Publication Date: 2020-07-03
XIANGYA HOSPITAL CENT SOUTH UNIV
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AI Technical Summary

Problems solved by technology

However, so far, there has been no report on the application of artificial intelligence image recognition technology to the prediction of the prognosis of burn wound images

Method used

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  • Artificial intelligence-based quick grading identification method and system for burn and scald images
  • Artificial intelligence-based quick grading identification method and system for burn and scald images

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Embodiment Construction

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

[0032] Embodiment of the present invention based on the artificial intelligence-based rapid classification recognition method for burn and scald images

[0033] Refer to attached figure 1 , the present embodiment uses standardized and graded database according to the healing situation, adopts artificial intelligence technology training to obtain a network classifier, and obtains an optimized burn and scald classification model, including the following steps,

[0034] (1) Collect burn and scald wound image photos and images: use the supporting image acquisition device 1 to collect 1000 photos and images of burn and scald patients’ wounds of uniform specifications, for backup;

[0035] (2) Grading and marking of photos and images: According to the actual healing time of the patient's wound surface, the photos and images are graded and marked, ...

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Abstract

The invention discloses an artificial intelligence-based quick grading identification method and system for burn and scald images. The method comprises the following steps: (1) collecting burn and scald wound photo images; (2) photo image grading marking; (3) obtaining a hierarchical database; (4) acquiring a network classifier, and establishing a burn and scald classification model; (5) optimizing a burn and scald grading model; (6) obtaining a burn and scald grading identification result; and (7) further expanding the original database after tracking the healing result of the new burn and scald wound photo image. The invention further comprises a matched hardware system for the method. By utilizing the method, the healing time range of wounds of burn and scald patients can be accuratelypredicted and graded, and doctors or patients can conveniently judge the illness state; an artificial intelligence algorithm based on a convolutional neural network is adopted, and along with continuous increase of the sample size and continuous optimization of the classification model, the prediction accuracy can be continuously improved.

Description

technical field [0001] The invention relates to the technical field of medical burn and scald image processing, in particular to an artificial intelligence-based method and system for rapidly grading and identifying burn and scald images. Background technique [0002] At present, about 20 million people in our country are burned to varying degrees every year, and the number of deaths caused by burns is second only to traffic accidents in accidental injuries. At the same time, burns and scalds often leave severe scars, resulting in disability and changes in appearance of patients, which have a huge impact on patients' life and psychology. [0003] Burns and scalds are divided into I degree, superficial II degree, deep II degree and III degree according to the different layers of skin affected by thermal injury. Burns and scalds of different degrees have different treatment methods and different prognosis. Early and correct diagnosis and classification are very important. How...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06T7/00G16H30/40G16H50/20
CPCG06T7/0012G16H50/20G16H30/40G06T2207/30088G06V10/955G06N3/045G06F18/214
Inventor 何志友魏天虹
Owner XIANGYA HOSPITAL CENT SOUTH UNIV
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