Title :
Rapid Multi-modality preRegistration based on SIFT descriptor
Author :
Chen, Jian ; Tian, Jie
Author_Institution :
Med. Image Process. Group, Chinese Acad. of Sci., Beijing
fDate :
Aug. 30 2006-Sept. 3 2006
Abstract :
This paper describes the scale invariant feature transform (SIFT) method for rapid preregistration of medical image. This technique originates from Lowe´s method wherein preregistration is achieved by matching the corresponding keypoints between two images. The computational complexity has been reduced when we applied SIFT preregistration method before refined registration due to its O(n) exponential calculations. The features of SIFT are highly distinctive and invariant to image scaling and rotation, and partially invariant to change in illumination and contrast, it is robust and repeatable for cursorily matching two images. We also altered the descriptor so our method can deal with multimodality preregistration
Keywords :
biomedical MRI; computational complexity; computerised tomography; image matching; image registration; medical image processing; CT; Lowe method; MRI; O(n) exponential calculations; computational complexity; image matching; image rotation; image scaling; medical image preregistration; rapid multimodality preregistration; scale invariant feature transform method; Biomedical imaging; Cities and towns; Computational complexity; Computer vision; Histograms; Image analysis; Image registration; Lighting; Robustness; USA Councils; Multi-modality; SIFT; keypoint; matching; preregistration;
Conference_Titel :
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location :
New York, NY
Print_ISBN :
1-4244-0032-5
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2006.260599