Browsing by Author "Argunsah A.O."

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3D dendritic spine segmentation using nonparametric shape priors
(Institute of Electrical and Electronics Engineers Inc., 2017) Bocugoz E.; Erdil E.; Argunsah A.O.; Unay D.; Cetin M.
Analyzing morphological and structural changes of dendritic spines in 2-photon microscopy images in time is important for neuroscience researchers. Correct segmentation of dendritic spines is an important step of developing robust and reliable automatic tools for such analysis. In this paper, we propose an approach for segmentation of 3D dendritic spines using nonparametric shape priors. The proposed method learns the prior distribution of shapes through Parzen density estimation on the training set of shapes. Then, the posterior distribution of shapes is obtained by combining the learned prior distribution with a data term in a Bayesian framework. Finally, the segmentation result that maximizes the posterior is found using active contours. Experimental results demonstrate that using nonparametric shape priors leads to better 3D dendritic spine segmentation results. © 2017 IEEE.
Coupled Shape Priors for Dynamic Segmentation of Dendritic Spines
(Institute of Electrical and Electronics Engineers Inc., 2017) Atabakilachini N.; Erdil E.; Argunsah A.O.; Rada L.; Unay D.; Cetin M.
Segmentation 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.