A dicom medical image sequence classification method for artificial intelligence-assisted diagnosis

An auxiliary diagnosis and artificial intelligence technology, applied in computer-aided medical procedures, medical images, healthcare informatics, etc., can solve problems such as wrong results, false positive results generated by artificial intelligence-assisted diagnosis, and no reference value, etc., to achieve correction The effect of identifying errors

Active Publication Date: 2020-11-10
BEIJING ANDE YIZHI TECH CO LTD
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AI Technical Summary

Problems solved by technology

Artificial intelligence will analyze a specific sequence or a collection of specific sequences in DICOM image data when assisting in diagnosis. If the wrong sequence is selected, it will usually lead to incorrect results or no reference value.
[0003] Application practice has proved that using some single methods based on daily experience (such as string comparison based on sequence names, or judgment based on metadata tags in DICOM) to classify DICOM sequences often leads to artificial intelligence-assisted diagnosis generating false positive results

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  • A dicom medical image sequence classification method for artificial intelligence-assisted diagnosis
  • A dicom medical image sequence classification method for artificial intelligence-assisted diagnosis

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[0020] The present invention is described in further detail now in conjunction with accompanying drawing. These drawings are all simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, so they only show the configurations related to the present invention.

[0021] This paper proposes a taxonomy suitable for artificial intelligence to correctly identify DICOM sequences. This classification method allows users to process sequence classification for different types of DICOM (generated by different hospitals, different imaging equipment and naming methods) according to their needs. Through the mixed strategy of multiple sequence classifiers, the user is allowed to operate for a period of time, and each result will be an update and supplement to the classifier, that is, to learn and train the auxiliary diagnostic system to correct the recognition error of a single method. This method specifically includes 5-layer cla...

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Abstract

The invention relates to a DICOM medical image sequence classification method for artificial intelligence-assisted diagnosis, which passes a DICOM data through five-layer classifiers in sequence, and finally obtains the classification result of a specific sequence. Through the mixed strategy of multiple sequence classifiers, the user can After operating for a period of time, each result is an update and supplement to the classifier, realizing the learning and training of the auxiliary diagnosis system to correct the recognition error of a single method.

Description

technical field [0001] The invention relates to a DICOM medical image sequence classification method for artificial intelligence-assisted diagnosis. Background technique [0002] The auxiliary diagnosis of medical images based on artificial intelligence related technologies such as deep neural networks can effectively improve the accuracy and efficiency of radiologists, clinicians and medical research in diagnosis and treatment. The basic principle of these artificial intelligence technologies is: select a specific sequence (such as T1, T2, DWIseries) of medical imaging data such as MRI and CT (following the DICOM data format specification) to train the artificial intelligence model, and then based on the trained model for other Medical imaging data for analysis and prediction. However, there is no mandatory requirement for the naming rules of medical image sequences in the DICOM protocol, and doctors and manufacturers are free to name the sequence descriptions. That is, t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G16H30/20G16H50/20
CPCG16H30/20G16H50/20G06F18/24G06F18/214
Inventor 韩荣强曾韦胜陈莹刘奎恩吴振洲
Owner BEIJING ANDE YIZHI TECH CO LTD
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