Title :
Region-based tracking of protein compounds
Author :
Wen, Q. ; Gao, J. ; Luby-Phelps, K.
Author_Institution :
Comput. Sci. & Eng., Texas Univ., Arlington, TX
Abstract :
Tagging and tracking protein compounds/compounds are key to a better understanding of proteomics such as protein-protein interaction and protein signaling pathway. In this paper, a generalized region tracking framework by statistical particle filter (PF) is presented for tracing the movement of protein compounds in confocal microscopy images. To effectively select the features to be tracked, a grid-based minimum variance spatial sampling method is developed. A similarity distance function is presented for feature correspondence finding. The experimental results demonstrate the tracking performance of the proposed framework for small size protein objects with irregular motions and large shape deformation in highly cluttered environment
Keywords :
biomechanics; biomedical optical imaging; deformation; grid computing; medical image processing; molecular biophysics; optical microscopy; particle filtering (numerical methods); proteins; sampling methods; confocal microscopy images; feature correspondence finding; grid-based minimum variance spatial sampling; irregular protein motions; large protein shape deformation; protein compounds; proteomics; region-based tracking; similarity distance function; statistical particle filter; Biomedical engineering; Computer science; Fluorescence; Mathematical model; Microscopy; Particle filters; Particle tracking; Protein engineering; Shape; Working environment noise;
Conference_Titel :
Biomedical Imaging: Nano to Macro, 2006. 3rd IEEE International Symposium on
Conference_Location :
Arlington, VA
Print_ISBN :
0-7803-9576-X
DOI :
10.1109/ISBI.2006.1624981