Seeded watersheds for combined segmentation and tracking
2005 (English)In: Image Analysis and Processing – ICIAP 2005, Springer Berlin / Heidelberg , 2005, Vol. 3617, 336-343 p.Chapter in book (Other academic)
Watersheds are very powerful for image segmentation, and seeded watersheds have shown to be useful for object detection in images of cells in vitro. This paper shows that if cells are imaged over time, segmentation results from a previous time frame can be used as seeds for watershed segmentation of the current time frame. The seeds from the previous frame are combined with morphological seeds from the current frame, and over-segmentation is reduced by rule-based merging, propagating labels from one time-frame to the next. Thus, watershed segmentation is used for segmentation as well as tracking of cells over time. The described algorithm was tested on neural stem/progenitor cells imaged using time-lapse microscopy. Tracking results agreed to 71% to manual tracking results. The results were also compared to tracking based on solving the assignment problem using a modified version of the auction algorithm.
Place, publisher, year, edition, pages
Springer Berlin / Heidelberg , 2005. Vol. 3617, 336-343 p.
, Lecture Notes in Computer Science, ISSN 0302-9743 ; 3617/2005
Computer and Information Science
IdentifiersURN: urn:nbn:se:uu:diva-98013DOI: 10.1007/11553595_41ISBN: 978-3-540-28869-5OAI: oai:DiVA.org:uu-98013DiVA: diva2:173169