Medical image classification processing system based on artificial intelligence

Abstract

The invention belongs to the technical field of medical image classification processing, and particularly relates to a medical image classification processing system based on artificial intelligence.The system comprises a local computer, a login unit, an image import unit, a central system image summarizing and collecting unit, a screening and classifying unit, a display unit and a terminal server. Image information of a focus of a current patient is obtained through the camera device, uploaded image data is subjected to label processing through the system and uploaded to the terminal server,data expansion and sharing are achieved, meanwhile, the image information of the patient is correspondingly compared with image information stored in the database, the case image information similarto the case image information is obtained through matching, medical image data shot by a patient can be accurately analyzed, a medical examination report is made, and therefore doctors are assisted inimproving the efficiency and accuracy of medical examination on the patient.

Description

technical field [0001] The invention relates to the technical field of medical image classification processing, in particular to an artificial intelligence-based medical image classification processing system. Background technique [0002] With the rapid development of modern medical imaging technology, medical imaging has become an important auxiliary diagnosis and treatment technology. However, with the integration of various medical imaging equipment such as CT, MR, DSA, DR, and a large number of computer technologies into the diagnosis, the effective use of medical imaging resources has become a very urgent problem. Hospitals generate a large number of medical images every day. If the image categories can be automatically marked, the workload of doctors can be greatly reduced, and the efficiency of medical images can also be improved. Medical image classification has become a very urgent need. [0003] Most of the traditional content-based image classification methods ...

AI Technical Summary

Problems solved by technology

[0005] First, accessing large, standardizedly formatted datasets with accurate results is a major challenge, although large clinical datasets from many institutions around the world are openly available, in a tractable and computational form, and accurate enough for learning tasks. The amount of data on the clinical diagnosis of the

From a global perspective, although the amount of data is huge, it is difficult to effectively use it; secondly, the existing equipment and the results of photographing have a huge amount of data, and the requirements for computer hardware are too high for a single institution to afford. At the same time, various institutions, hospitals They all try to build their own models and systems, but there are regional barriers, which prevent the effective sharing of medical resources and hinder the accuracy of deep learning; finally, the existing equipment cannot provide similar cases for uploaded medical images in a timely manner. It is impossible to assist doctors to improve the efficiency and accuracy of medical examinations for patients. Therefore, it is necessary to develop a medical image classification and processing system based on artificial intelligence.

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