Medical cloud platform-based image big data analysis system and method

Abstract

The invention discloses a medical cloud platform-based image big data analysis system and method, which is applied to a cloud server. The cloud server is connected with an image collection terminal, a medial cloud platform and a doctor diagnosis and treatment terminal through a communication network. The image collection terminal comprises an input unit, an infrared generator, an infrared receiver, an analog-to-digital converter and a communication port. The image big data analysis system comprises a user information obtaining module, an image collection module, an image processing module, an image analysis module and a body local organ image output module. An examination image of a user is collected through the image collection terminal, so that the user can perform body local organ health screening conveniently and hospital resources are saved; and by performing noise removal and grayscale hierarchical processing on the examination image, body local organ texture features are extracted from the examination image to provide a reference for a doctor to perform diagnosis and screening on body local organ diseases, thereby assisting the doctor to improve the efficiency and accuracy of screening the body local organ diseases.

Description

technical field [0001] The invention relates to the technical field of medical image processing and recognition, in particular to an image big data analysis system and method based on a medical cloud platform. Background technique [0002] At present, the use of examination images for auxiliary diagnosis has become an important method for screening and diagnosing early stage cancer in local organs of the body. At present, when computer-aided detection methods are used to detect and screen local body organs on inspection images, doctors usually need to manually draw the approximate range of suspicious regions (ROIs) of local body organs on the images of local body organs. Screening and detection of local body organs The efficiency is not high, and it is not suitable for the census of a large number of body part organ samples. During the physical examination and census activities of partial body organs, patients need to come to the partial body organ census center or hospital...

AI Technical Summary

Problems solved by technology

At present, when using computer-aided detection methods to detect and screen local body organs on inspection images, doctors usually need to manually draw the approximate range of suspicious regions (ROIs) of local body organs on the images of local body organs. Screening and detection of local body organs The efficiency is not high, and it is not suitable for the census of a large number of body part organ samples

During the physical examination and census of body parts, patients need to come to the body parts census center or hospital in person, causing a large number of people to queue up and straining the originally limited hospital resources.

In addition, due to the large number of images of body parts, it is difficult for doctors to manually draw ROIs on each part of the body for detection, which is difficult to ensure efficiency and accuracy, which may easily lead to missed and misdiagnosed cases.

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