Longitudinal partition ultrasonic endoscope image real-time auxiliary diagnosis system and method based on deep learning

A technology of deep learning and auxiliary diagnosis, applied in the field of image recognition, can solve problems such as limited experience, difficulty in identifying mediastinal lesions in ultrasound endoscopic images, missed diagnosis and misdiagnosis, etc., to avoid misdiagnosis and missed diagnosis, save time and energy, and improve accuracy and the effect of effectiveness

Pending Publication Date: 2019-04-12
武汉大学人民医院
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Problems solved by technology

Doctors with less qualifications may have difficulty identifying mediastinal lesions in endoscopic

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  • Longitudinal partition ultrasonic endoscope image real-time auxiliary diagnosis system and method based on deep learning
  • Longitudinal partition ultrasonic endoscope image real-time auxiliary diagnosis system and method based on deep learning

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[0016] In order to facilitate the understanding and implementation of the present invention by those of ordinary skill in the art, the present invention will be further described in detail with reference to the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0017] Please see figure 1 , The present invention provides a real-time auxiliary diagnosis system for mediastinal ultrasound endoscopic images based on deep learning, which includes an image acquisition module, a communication module, and a lesion recognition module;

[0018] The image acquisition module is used to acquire pictures and videos obtained by using ultrasound endoscopy equipment for mediastinal examination, and decode the videos into pictures;

[0019] The lesion recognition module is used to receive the picture of the image acquisition module, d...

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Abstract

The invention discloses a longitudinal partition ultrasonic endoscope image real-time auxiliary diagnosis system and method based on deep learning. The system comprises an image acquisition module, acommunication module and a focus recognition module. The image acquisition module is used for acquiring a picture and a video which are obtained by performing longitudinal partition inspection by using ultrasonic endoscope equipment and decoding the video into a picture; the focus recognition module is used for receiving the picture of the image acquisition module, judging features corresponding to the image in time and obtaining a disease recognition and classification result; and the image acquisition module and the focus recognition module are connected and communicated through the communication module. According to the invention, an image acquisition module is firstly used for acquiring longitudinal ultrasonic endoscope pictures and videos; taking the mediastinal ultrasound endoscopy picture as a parameter, and calling a convolutional neural network model to identify and classify the disease; and finally, receiving a classification result of the convolutional neural network model,and assisting doctors in disease diagnosis. According to the method, the detection accuracy and effectiveness are improved, the misdiagnosis missed diagnosis occurrence probability is reduced, and thelabor cost is saved.

Description

technical field [0001] The invention belongs to the technical field of image recognition, and relates to a real-time auxiliary diagnosis system and method, in particular to a real-time auxiliary diagnosis system and method for mediastinal ultrasound endoscopic images based on deep learning. Background technique [0002] Endoscopic ultrasonography (EUS) is a digestive tract examination technology that combines endoscopy and ultrasound. Observation of organ and tissue structure improves the diagnostic level of endoscopy and ultrasound. Compared with CT, MRI, and PET-CT imaging diagnostic methods, endoscopic ultrasonography has certain advantages in the diagnosis of mediastinal diseases. Doctors judge the imaging characteristics of endoscopic ultrasonography, such as lesion length, echo characteristics, boundaries, vascular infiltration, and surrounding tissues. Mediastinal tuberculosis, mediastinal sarcoidosis, mediastinal and hilar lymphadenopathy, etc. [0003] In the diag...

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Application Information

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IPC IPC(8): G16H50/20G06K9/62
CPCG16H50/20G06V2201/03G06F18/214
Inventor 于红刚张军吴练练胡珊宫德馨
Owner 武汉大学人民医院
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