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Deep learning-based intelligent X-ray film diagnosis method

A technology of intelligent diagnosis and deep learning, applied in the field of medical image recognition, can solve problems such as difficult-to-diagnose lung diseases, and achieve the effect of saving time and accurate prediction

Inactive Publication Date: 2018-11-27
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, the object of the present invention is to provide an intelligent diagnosis method based on deep learning of X-ray films, which can solve the problem in the prior art that manual identification of X-ray films is difficult to diagnose the performance of lung diseases

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  • Deep learning-based intelligent X-ray film diagnosis method

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Embodiment Construction

[0041] Below, in conjunction with accompanying drawing and specific embodiment, the present invention is described further:

[0042] like figure 1 As shown, the present invention provides a method for intelligent diagnosis of X-ray film based on deep learning, which specifically includes the following steps:

[0043] S1: Obtain the image data of the chest X-ray film stored in the preset memory;

[0044] In the present invention, deep learning of data is the key. The preset memory shown in the present invention is not necessarily an actual electronic device, but only indicates that the influencing data comes from a certain or some storage intervals. The influencing data of the present invention It can come from a research institute or the chest X-ray database ChestX-ray14, which contains 14 kinds of lung diseases (atelectasis, consolidation, infiltration, pneumothorax, edema, emphysema, fibrosis, effusion, pneumonia , pleural thickening, cardiac hypertrophy, nodules, masses a...

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Abstract

The invention discloses a deep learning-based intelligent X-ray film diagnosis method. The method comprises the following steps: image data of chest X-ray films stored in a preset memory are acquired;the image data of the chest X-ray films are augmented in a preset mode; the augmented image data are subjected to preprocessing operation to enable data features to meet a standard; the preprocessedimage data are classified to form a plurality of classification models, and model training is designed for each classification model to generate a model training prediction result; a final CNN featuremap is acquired, and according to the CNN feature map, a thermodynamic map is generated; and according to the model training prediction result of each classification model, an integration result is calculated and obtained. Deep learning on pulmonary disease characteristics in a large number of chest X-ray films can be carried out, multiple pulmonary diseases can be accurately predicted, a diagnosis basis is provided, the prediction time is greatly less than manual diagnosis time, and the time of a doctor is saved.

Description

technical field [0001] The invention relates to medical image recognition technology, in particular to an X-ray intelligent diagnosis method based on deep learning. Background technique [0002] Chest x-rays are the most commonly used medical imaging tool and play a vital role in the screening, diagnosis and management of diseases including pneumonia, however monitoring lung disease from chest x-rays A difficult task for radiologists. Because lung disease is often difficult to identify on x-rays, it may overlap with other conditions and can mimic many other benign abnormalities. These reasons lead to wide variation in the performance of radiologists when diagnosing lung disease. Contents of the invention [0003] In order to overcome the deficiencies of the prior art, the object of the present invention is to provide a deep learning-based X-ray film intelligent diagnosis method, which can solve the problem in the prior art that manual identification of X-ray films is dif...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/20G06N3/02
CPCG06N3/02G16H50/20
Inventor 周志光马力
Owner 中山仰视科技有限公司
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