title: Employing temporal information for cell segmentation using max-flow/min-cut in phase-contrast video microscopy.
abstract: Cell segmentation is a crucial step in many bio-medical image analysis applications and it can be considered as an important part of a tracking system. Segmentation in phase-contrast images is a challenging task since in this imaging technique, the background intensity is approximately similar to the cell pixel intensity. In this paper we propose an interactive automatic pixel level segmentation algorithm, that uses temporal information to improve the segmentation result. This algorithm is based on the max-flow/min-cut algorithm and can be solved in polynomial time. This method is not restricted to any specific cell shape and segments cells of various shapes and sizes. The results of the proposed algorithm show that using the temporal information does improve segmentation considerably.
authors.affiliation: Department of Computer Science and Engineering, University of New South Wales, Sydney, New South Wales 2052, Australia.
authors.forename: Amir
authors.initials: A
authors.lastname: Massoudi
authors.forename: Arcot
authors.initials: A
authors.lastname: Sowmya
authors.forename: Katarina
authors.initials: K
authors.lastname: Mele
authors.forename: Dimitri
authors.initials: D
authors.lastname: Semenovich
mesh_terms: D000465:Algorithms; D058948:Cell Tracking / Q000379:methods*; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008858:Microscopy, Phase-Contrast / Q000379:methods*; D018715:Microscopy, Video / Q000379:methods*; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique