Cancer image prediction and discrimination method and system based on transfer learning

Abstract

The invention discloses a cancer image prediction and discrimination method and system based on transfer learning. The method comprises two parts of training of a transfer learning model and image classification based on the transfer learning model. The first part comprises construction of a transfer learning model, construction of a data set and training and storage of the transfer learning model, and the second part comprises the steps: inputting an image to be judged for category prediction by loading a transfer learning classification model stored in the first part. The system comprises atleast one processor; at least one memory which is used for storing at least one running program and the to-be-identified medical image; when the program runs in the processor, at least one processoris enabled to realize prediction and identification of the medical image. The method and system are used for intelligent analysis and discrimination of medical image big data, and provides rapid and relatively accurate medical auxiliary diagnosis, thereby improving the accuracy and efficiency of clinical diagnosis.

Description

technical field [0001] The invention belongs to the field of medical image data processing, and in particular relates to a cancer image prediction and discrimination method and system based on migration learning. Background technique [0002] With the rapid development of computer storage capacity and computing power, artificial intelligence related technologies have been greatly developed, especially related technologies of natural language processing and computer vision. [0003] Nowadays, the wave of artificial intelligence is sweeping across various industries. With the improvement of people's living standards and the arrival of population aging, people's demand for health is increasing, which makes the medical industry face the problem that the supply of medical resources cannot be fully To meet the needs of the public for high-level medical care, such as the shortage of radiologist resources, because the existing cancer screening analysis is based on medical tests, and...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to overcome the low efficiency of the above-mentioned working method of discriminating cancer images by human beings, which requires more manpower and material resources, and provides a method and system for predicting and discriminating cancer images based on transfer learning, which is used for large-scale medical imaging. Intelligent analysis and discrimination of data to provide fast and relatively accurate medical aided diagnosis, thereby improving the accuracy and efficiency of clinical diagnosis

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