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Start date: 2010End date: 2019Type: search.filters.itemtype.Conference PaperSubject: search.filters.subject.Signal processingAuthor: search.filters.author.Ünay, DevrimAuthor: search.filters.author.Çetin, Müjdat

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    A watershed and active contours based method for dendritic spine segmentation in 2-photon microscopy images, 2-Foton mikroskopi görüntülerindeki dendritik dikenlerin bölütlenmesi için watershed ve etkin çevritlere dayali bir yöntem
    (2013) Erdil, Ertunç; Argunşah, Ali Özgür; Ünay, Devrim; Çetin, Müjdat; Erdil, Ertunç, Mühendislik ve Doǧa Bilimleri Fakültesi, Sabancı Üniversitesi, Tuzla, Turkey; Argunşah, Ali Özgür, Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal; Ünay, Devrim, Bahçeşehir Üniversitesi, Istanbul, Turkey; Çetin, Müjdat, Mühendislik ve Doǧa Bilimleri Fakültesi, Sabancı Üniversitesi, Tuzla, Turkey
    Analysing morphological and volumetric properties of dendritic spines from 2-photon microscopy images has been of interest to neuroscientists in recent years. Developing robust and reliable tools for automatic analysis depends on the segmentation quality. In this paper, we propose a new segmentation algorithm for dendritic spine segmentation based on watershed and active contour methods. First, our proposed method coarsely segments the dendritic spine area using the watershed algorithm. Then, these results are further refined using a region-based active contour approach. We compare our results and the results of existing methods in the literature to manual delineations of a domain expert. Experimental results demonstrate that our proposed method produces more accurate results than the existing algorithms proposed for dendritic spine segmentation. © 2013 IEEE. © 2013 Elsevier B.V., All rights reserved.
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    Automated dendritic spine tracking on 2-photon microscopic images, 2-Foton Mikroskopi Goriintiilerinde Otomatik Dendritik Diken Takibi
    (Institute of Electrical and Electronics Engineers Inc., 2015) Kilic, Bike; Rada, Lavdie; Erdil, Ertunç; Argunşah, Ali Özgür; Çetin, Müjdat; Ünay, Devrim; Kilic, Bike, Bahçeşehir Üniversitesi, Istanbul, Turkey; Rada, Lavdie, Bahçeşehir Üniversitesi, Istanbul, Turkey; Erdil, Ertunç, Sabancı Üniversitesi, Tuzla, Turkey; Argunşah, Ali Özgür, Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal; Çetin, Müjdat, Sabancı Üniversitesi, Tuzla, Turkey; Ünay, Devrim, Bahçeşehir Üniversitesi, Istanbul, Turkey
    The rapid and spontaneous morphological changes of dendritic spines have been an important observation to understand how information is stored in brain. Manual assessment of spine structure has been a useful tool to understand the differences between wild type (normal) and diseased cases. In order to perform a more through analysis, automatic tools need to be developed due to the immense amount of image data collected throughout the experiments. Additionally, dendritic spines are very dynamic structures and florescence microscopy contains high level of noise, blur and shift due to the optical properties. In this study, we track locations of dendritic spines in a full series of a time-lapse two photon microscopic images. To achieve this we propose a combined detection and tracking framework. For the detection we use a SIFT based algorithm, while the tracking requires a combination of registration and distance based spine matching. Experimental results show that this technique helps to track detected spines in time series even though the noise or blur deformed the image and complicated the detection. © 2021 Elsevier B.V., All rights reserved.
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    Coupled shape priors for dynamic segmentation of dendritic spines
    (Institute of Electrical and Electronics Engineers Inc., 2017) Atabakilachini, Naeimeh; Erdil, Ertunç; Argunşah, Ali Özgür; Rada, Lavdie; Ünay, Devrim; Çetin, Müjdat; Atabakilachini, Naeimeh, Faculty of Engineering and Natural Sciences, Sabancı Üniversitesi, Tuzla, Turkey; Erdil, Ertunç, Faculty of Engineering and Natural Sciences, Sabancı Üniversitesi, Tuzla, Turkey; Argunşah, Ali Özgür, University of Zurich, Brain Research Institute, Zurich, Switzerland; Rada, Lavdie, Faculty of Engineering and Natural Sciences, Bahçeşehir Üniversitesi, Istanbul, Turkey; Ünay, Devrim, Department of Biomedical Engineering, Izmir Ekonomi Üniversitesi, Izmir, Turkey; Çetin, Müjdat, Faculty of Engineering and Natural Sciences, Sabancı Üniversitesi, Tuzla, Turkey
    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 Elsevier B.V., All rights reserved.