Nuclear magnetic resonance image classification method based on multi-strategy batch type active learning

Abstract

The invention discloses a nuclear magnetic resonance image classification method based on multi-strategy batch type active learning and belongs to the field of intelligent medical diagnosis. The method comprises the following steps: obtaining a nuclear magnetic resonance image of the subject as an original data set; randomly selecting K samples from the unlabeled sample set; labeling, constructinga convolutional neural network model and a convolutional auto-encoder model; verifying the convolutional neural network model trained again by using the verification set; obtaining a trained convolutional neural network model; and inputting the unlabeled test set into the trained convolutional neural network model to obtain a final classification result of the nuclear magnetic resonance images ofthe three types of subjects with normal cognition, mild cognitive impairment and Alzheimer's disease, so that redundant information among the screened samples is relieved, and high-quality labeled samples are obtained. On the premise of ensuring high classification accuracy, the labeling cost of the nuclear magnetic resonance image is reduced, and a doctor is efficiently assisted in diagnosing the Alzheimer's disease.

Description

technical field [0001] The invention relates to the field of intelligent medical diagnosis, in particular to a method for classifying nuclear magnetic resonance images based on multi-strategy batch active learning. Background technique [0002] Alzheimer's disease (AD), also known as senile dementia, is an irreversible neurodegenerative disease of the brain. AD occurs frequently in the elderly, and patients are usually accompanied by symptoms such as memory loss and cognitive impairment. Generally, the diagnosis of Alzheimer's disease can be regarded as a classification problem, that is, to judge whether a subject belongs to the category of cognitive normal, mild cognitive impairment and Alzheimer's disease. [0003] At present, magnetic resonance imaging (Magnetic Resonance Imaging, MRI) has been widely used in the clinical diagnosis of Alzheimer's disease. MRI is a 3D image composed of a series of 2D slice images. It has the characteristics of high resolution, high contra...

AI Technical Summary

Problems solved by technology

However, the traditional batch active learning method only uses a single uncertainty strategy or diversity strategy for screening when screening samples, resulting in a large amount of redundant information in the screened samples, resulting in additional labeling costs.

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