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DR-based pulmonary tuberculosis intelligent identification method and system

A technology for intelligent recognition and tuberculosis, applied in the field of image recognition, can solve the problems of low penetration rate, long time consumption, low efficiency and so on

Inactive Publication Date: 2018-02-23
江西中科九峰智慧医疗科技有限公司
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Problems solved by technology

[0005] However, existing HRCT has high cost, low penetration rate, and poor practicability
As a result, the existing tuberculosis screening basically relies on purely manual film reading, which is not only costly, inefficient, and time-consuming; but also relies heavily on the doctor's personal experience when manually identifying and reading films. There is a phenomenon of missed diagnosis

Method used

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  • DR-based pulmonary tuberculosis intelligent identification method and system
  • DR-based pulmonary tuberculosis intelligent identification method and system
  • DR-based pulmonary tuberculosis intelligent identification method and system

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Embodiment Construction

[0028] In order to make the technical means, creative features, goals and effects achieved by the present invention easy to understand, the present invention will be further described below in conjunction with specific illustrations.

[0029] For the automatic screening of pulmonary tuberculosis, this example scheme realizes the intelligent identification of pulmonary tuberculosis based on DR, which is low in cost and high in efficiency, and can effectively avoid the phenomenon of missed detection and unrecognized.

[0030] On this basis, this example scheme adopts the deep learning method to independently learn the image features of tuberculosis in DR images, so as to realize accurate identification and effectively improve the identification accuracy.

[0031] Specifically, this solution uses a large number of manually labeled samples to train a deep neural network, so that it can learn the image features of tuberculosis autonomously, thereby identifying the image features of ...

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Abstract

The present invention discloses a DR-based pulmonary tuberculosis intelligent identification method and system. The method is characterized in that: a deep neural network is formed and trained by using a large number of manually labeled samples, and the deep neural network identifies pulmonary tuberculosis image feature in a DR image through self-learning of the pulmonary tuberculosis image features. The resulting pulmonary tuberculosis intelligent identification method can realize automatic identification of the pulmonary tuberculosis image features in the DR image, can realize automatic screening of the DR-based pulmonary tuberculosis, and can effectively reduce the screening cost; and furthermore, the scheme has high recognition efficiency and high recognition accuracy, can effectivelyavoid misdetection and unidentification, and can effectively solve the problem existing in the prior art.

Description

technical field [0001] The invention relates to image recognition technology, in particular to the recognition technology of DR images. Background technique [0002] Pulmonary tuberculosis (PTB) is a pulmonary infectious disease caused by Mycobacterium tuberculosis, a serious threat to human health. Statistics from the World Health Organization (WHO) show that 8 to 10 million cases of tuberculosis occur in the world every year, and about 3 million people die from tuberculosis every year. It is the single infectious disease that causes the largest number of deaths. In 1993, WHO declared a "global tuberculosis emergency", arguing that tuberculosis has become an important public health problem all over the world. China is one of the countries with the worst tuberculosis epidemic in the world. [0003] Existing CAD systems are typically based on high-resolution thin-section computed tomography (HRCT) images, automatically morphologically detecting (identifying) a site of inter...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06N3/08
CPCG06N3/084G06V2201/031G06F18/214
Inventor 吴文辉陶信东
Owner 江西中科九峰智慧医疗科技有限公司
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