Nerve dendritic spine image classification method based on multiresolution fractal features

Abstract

The invention discloses a nerve dendritic spine image classification method based on multiresolution fractal features. The method includes the following steps of (1) extracting features of nerve dendritic spine images to obtain the multiresolution fractal features of the nerve dendritic spine images; and (2) classifying the nerve dendritic spine images based on the multiresolution fractal features of the nerve dendritic spine images in the method of linear discriminant analysis (LDA). According to the method, classification precision is high and classification results are stable.

Description

technical field [0001] The invention belongs to the field of intelligent image analysis, in particular to a high-reliability classification method for neural dendritic spine images, in particular to a neural dendritic spine image classification method based on multi-resolution fractal features. Background technique [0002] In recent years, cell microscope imaging technology has been developed rapidly. Brain neuron imaging is crucial to understanding neuron morphology and neuron movement mechanism, especially in the study of many diseases, exploring the dynamic response of neurons to complex perception and motor processes is an important means. Brain neuron imaging plays an important role in these The research reflects its irreplaceable important position. There is no doubt that microscopic imaging has become an important tool for breakthrough research in various neurological diseases. [0003] Although many breakthroughs have been made in microscope imaging technology, th...

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Problems solved by technology

[0005] The purpose of the present invention is to provide a neural dendritic spine image classification method based on multi-resolution fractal features, which solves the problems of poor image classification effect and poor classification accuracy in the prior art.

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