Integrated learning grading method for new coronal pneumonia, electronic equipment and storage medium

An integrated learning and grading technology, applied in the field of data processing, can solve the problems of relying on CT data viewing and relying on viewing, and achieve the effect of improving model performance, making full use of it, and preventing large deviations

Active Publication Date: 2020-08-07
中山仰视科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In order to overcome the deficiencies of the prior art, one of the purposes of the present invention is to provide an integrated learning grading method for COVID-19, which can solve the problem of relying on manual inspection of CT data in the prior art
[0004] The second object of the present invention is to provide an electronic device, which can solve the problem of relying on manual inspection of CT data in the prior art
[0005] The third object of the present invention is to provide a storage medium, which can solve the problem of relying on manual inspection of CT data in the prior art

Method used

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  • Integrated learning grading method for new coronal pneumonia, electronic equipment and storage medium
  • Integrated learning grading method for new coronal pneumonia, electronic equipment and storage medium
  • Integrated learning grading method for new coronal pneumonia, electronic equipment and storage medium

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0033] This embodiment provides an integrated learning grading method for COVID-19, such as figure 1 As shown, this embodiment includes the following steps:

[0034] S1: Obtain CT data of several patients and preprocess the CT data to generate lung window data in a set format.

[0035] The embodiment of the present invention is used to detect lung CT of a suspected patient. Maybe enough training data before building the model. The training data can be obtained by collecting lung CT of patients who have been diagnosed as CT data for processing. By detecting the lung CT of a suspected patient, it is judged whether it is infected with new coronary pneumonia, and the degree of infection is given. According to different grades, doctors can judge whether the patient needs further detection and treatment according to the graded results, so as to make full use of it. Medical resources, so that more resources can be used for patients who need it more, and avoid unnecessary waste.

...

Embodiment 2

[0062] This embodiment provides an electronic device on which a memory, a processor, and a computer-readable program stored in the memory and executable by the processor are stored, wherein the computer-readable program is processed by the processor , implement the following steps:

[0063] Obtain CT data of several patients and preprocess the CT data to generate lung window data in a set format;

[0064] Input the grading parameters of pneumonia symptoms, and build an integrated learning framework based on the ordered regression residual network;

[0065] Input the lung window data into the integrated learning framework for training to output a training model;

[0066] Inputting new CT data into the training model to output the pneumonia symptom grading result corresponding to the CT data.

Embodiment 3

[0068] This embodiment provides a storage medium on which is stored a computer-readable program executable by a processor, wherein when the computer-readable program is processed by the processor, the following steps are implemented:

[0069] Obtain CT data of several patients and preprocess the CT data to generate lung window data in a set format;

[0070] Input the grading parameters of pneumonia symptoms, and build an integrated learning framework based on the ordered regression residual network;

[0071] Input the lung window data into the integrated learning framework for training to output a training model;

[0072] Inputting new CT data into the training model to output the pneumonia symptom grading result corresponding to the CT data.

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Abstract

The invention discloses an ensemble learning grading method for new coronal pneumonia, and the method comprises the following steps: acquiring CT data of a plurality of patients and preprocessing theCT data to generate lung window data in a set format; constructing an ensemble learning framework based on an ordered regression residual network; inputting the lung window data into an ensemble learning framework for training so as to output a training model; and inputting new CT data into the training model so as to output a pneumonia disease grading result corresponding to the CT data. The ensemble learning framework built by the invention adopts the ordered regression regularization, and combines the ordered structure between the new coronal pneumonia grading data, so the ordered structurebetween the data can be learned, the model performance is improved, the large deviation of model prediction is prevented, and the data result output is more accurate.

Description

technical field [0001] The present invention relates to data processing technology, in particular to an integrated learning grading method for COVID-19, electronic equipment and storage media. Background technique [0002] The main difficulty of COVID-19 is that it is difficult to detect. Nucleic acid testing is currently the most important basis for the diagnosis of patients. At this time, effective clinical indicators and experience have become important reference indicators. Chest CT is a routine tool for diagnosing pneumonia. The examination speed is fast, and the images can be used for various purposes such as detection of pneumonia lesions, judgment of nature, extent of involvement, and evaluation of diagnosis and treatment. At the same time, in this new coronary pneumonia, the lung infection changes rapidly. On the imaging, it mainly shows the distribution of outer bands, multi-lobe segments, and ground-glass interstitial changes, and changes appear within two or thre...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/62G06N3/04G06N3/08G16H30/20G16H50/20G16H50/70
CPCG06T7/0012G06N3/08G16H30/20G16H50/20G16H50/70G06T2207/10081G06T2207/20081G06T2207/20084G06T2207/30061G06T2207/30064G06T2207/30096G06N3/045G06F18/241
Inventor 陈任政滕达黄钰斌汪方军马力王艳芳陈庆武
Owner 中山仰视科技有限公司
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