[A fast 3-D medical image registration algorithm using principal component analysis].
This paper presents a new 3-D image registration method based on the principal component analysis (PCA). Compared with intensity-based registration methods using the whole volume intensity information, our approach utilizes PCA to estimate the centroid and principal axis, and completes the registration by aligning the centroid and principal axis. We evaluated the effectiveness of this approach by applying it to simulated and actual brain image data (MR, CT, PET, and SPECT). The experimental results indicate that the algorithm is effective, especially for registration of 3-D medical images.
Lu
Zhen-tai
ZT
Institute of Medical Information, School of Biomedical Engineering, Southern Medical University, Guangzhou, China. luzhentai@163.com
Chen
Wu-fan
WF
D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging; D003952:Diagnostic Imaging / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging; D049268:Positron-Emission Tomography; D025341:Principal Component Analysis; D011859:Radiography; D011881:Radiotherapy, Computer-Assisted; D015203:Reproducibility of Results