Atabakilachini N.Erdil E.Argunsah A.O.Rada L.Unay D.Cetin M.2023-06-162023-06-1620179.78E+12https://doi.org/10.1109/SIU.2017.7960599https://hdl.handle.net/20.500.14365/360425th Signal Processing and Communications Applications Conference, SIU 2017 -- 15 May 2017 through 18 May 2017 -- 128703Segmentation of biomedical images is a challenging task, especially when there is low quality or missing data. The use of prior information can provide significant assistance for obtaining more accurate results. In this paper we propose a new approach for dendritic spine segmentation from microscopic images over time, which is motivated by incorporating shape information from previous time points to segment a spine in the current time point. In particular, using a training set consisting of spines in two consecutive time points to construct coupled shape priors, and given the segmentation in the previous time point, we can improve the segmentation process of the spine in the current time point. Our approach has been evaluated on 2-photon microscopy images of dendritic spines and its effectiveness has been demonstrated by both visual and quantitative results. © 2017 IEEE.eninfo:eu-repo/semantics/openAccess2-photon microscopycoupled shape priorsdendritic spine segmentationDynamic segmentationnonparametric shape priorsPhotonsSignal processingBiomedical imagesDendritic spineDynamic segmentationPrior informationQuantitative resultSegmentation processShape informationShape priorsImage segmentationConference Object10.1109/SIU.2017.79605992-s2.0-85026319344