Medical image feature extraction and visualization based on principal component analysis

ABSTRACT

In view of the problem that it is difficult to extract and analyze the medical image feature information, this paper investigates a feature extraction and visualization method of medical image based on principal component analysis. Firstly, the medical image feature extraction and space conversion mechanism is analyzed, and the feature information from the original spatial dimensions of medical images is extracted by using PCA technology. Then the extracted feature image is effectively reconstructed and visualized. The method is verification through COVID-19 CT images, results show that when the cumulative contribution rate of the principal component reaches 85%, the principal component analysis method can restore the information of the original image more clearly, and realize the feature extraction and visual reconstruction of medical images. © 2021 IEEE.