| Title | A hybrid approach for arabidopsis root cell image segmentation |
| Publication Type | Book |
| Year of Publication | 2008 |
| Authors | Marcuzzo, M, Quelhas, P, Campilho, A, Mendonça, AM, Campilho, A |
| Series Title | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Lect. Notes Comput. Sci. |
| Volume | 5112 LNCS |
| Number of Pages | 739 - 749 |
| City | Povoa de Varzim |
| ISBN Number | 03029743 (ISSN); 3540698116 (ISBN); 9783540698111 (ISBN) |
| Keywords | Arabidopsis (Arabidopsis thaliana), Arabidopsis thaliana (ELIP), Cell divisions, Cell image segmentation, cell proliferation, Cell segmentation, Cells, confocal microscopy, Digital image storage, Heidelberg (CO), Hybrid approaches, Image analysis, Image data, image processing, Image segmentation, Imaging techniques, In vivo observation, Individual (PSS 544-7), International conferences, Merging, Microscopic examination, Research tools, Root meristem, Strength (IGC: D5/D6), Support Vector Machine (SVM), Support vector machines, Time lapse confocal microscopy |
| Abstract | In vivo observation and tracking of the Arabidopsis thaliana root meristem, by time-lapse confocal microscopy, is important to understand mechanisms like cell division and elongation. The research herein described is based on a large amount of image data, which must be analyzed to determine the location and state of cells. The automation of the process of cell detection/marking is an important step to provide research tools for the biologists in order to ease the search for special events, such as cell division. This paper discusses a hybrid approach for automatic cell segmentation, which selects the best cell candidates from a starting watershed-based image segmentation and improves the result by merging adjacent regions. The selection of individual cells is obtained using a Support Vector Machine (SVM) classifier, based on the shape and edge strength of the cells' contour. The merging criterion is based on edge strength along the line that connects adjacent cells' centroids. The resulting segmentation is largely pruned of badly segmented and over-segmented cells, thus facilitating the study of cell division. © 2008 Springer-Verlag Berlin Heidelberg. |
| URL | http://www.scopus.com/inward/record.url?eid=2-s2.0-47749134578&partnerID=40&md5=3b05fc0d5d004216e681d9c3e2199aac |
