DocumentCode :
1821460
Title :
Automatic registration of large set of microscopic images using high-level features
Author :
Prescott, Jeffrey ; Clary, Matthew ; Wiet, Gregory ; Pan, Tony ; Huang, Kun
Author_Institution :
Dept. of Electr. & Comput. Eng., Ohio State Univ., Columbus, OH
fYear :
2006
fDate :
6-9 April 2006
Firstpage :
1284
Lastpage :
1287
Abstract :
In this paper, we present a novel method for automatic registration of large set of microscopic images by automatically match high-level region features via finding cyclic structures in a matching graph. The use of high-level features (e.g., regions, landmarks, objects) significantly reduced the computation and provides accurate initialization, which further allows fast convergence of the maximum mutual information algorithm. The scheme is a universal one as it works for other types of high-level features and the matching process is very computationally efficient. We have applied our method in 3-D reconstruction of a unique human cochlear sample and are also applying it to two other set of large microscopic images
Keywords :
ear; image matching; image reconstruction; image registration; medical image processing; 3-D reconstruction; automatic microscopic image registration; cyclic structures; high-level features; human cochlear sample; matching graph; maximum mutual information algorithm; Biomedical informatics; Computer vision; Convergence; Ear; Humans; Microscopy; Mutual information; NP-complete problem; Three dimensional displays; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging: Nano to Macro, 2006. 3rd IEEE International Symposium on
Conference_Location :
Arlington, VA
Print_ISBN :
0-7803-9576-X
Type :
conf
DOI :
10.1109/ISBI.2006.1625160
Filename :
1625160
Link To Document :
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