Medical Image Feature Extraction and Registration Algorithm Based on PCA

Abstract

In order to improve the accuracy and speed of medical image registration, a PCA based medical image feature extraction and registration algorithm is proposed. Firstly, the original image is trained and the sample matrix is generated. Then, the dimension of the sample image is reduced from the high dimensional space to the low dimensional space by using the linear transformation of principal component analysis. Finally, the image registration in low dimensional space is performed by combining the image registration algorithm of rigid transformation. Clinical experimental data show that the proposed algorithm has high speed and accuracy, which can not only significantly improve the image registration speed, but also remove the artifacts and retain the image feature information in clinical significance to the maximum extent, which provides an effective help for disease diagnosis and treatment.