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Publication Metadata only Air drums: A computer vision based drums simulator, Bilgisayarla görü tabanli davul benzetimcisi(2010) Fidan, Kaan Can; Kehribar, İhsan; Şahin, M. Tuǧçe; Cosar, Serhan; Ünay, Devrim; Fidan, Kaan Can, Mühendislik ve Doǧa Bilimleri Fakültesi, Sabancı Üniversitesi, Tuzla, Turkey; Kehribar, İhsan, Mühendislik ve Doǧa Bilimleri Fakültesi, Sabancı Üniversitesi, Tuzla, Turkey; Şahin, M. Tuǧçe, Mühendislik ve Doǧa Bilimleri Fakültesi, Sabancı Üniversitesi, Tuzla, Turkey; Cosar, Serhan, Mühendislik ve Doǧa Bilimleri Fakültesi, Sabancı Üniversitesi, Tuzla, Turkey; Ünay, Devrim, Bahçeşehir Üniversitesi, Istanbul, TurkeyThe aim of this paper is to present a novel system which tracks the motion of a drummer and generates the corresponding drum sounds. The input video sequence from a camera is processed in real-time by using local and adaptive color segmentation and Kalman filter based tracking. The Kalman filter is used to predict the hits so that we can overcome the processing delays and provide a more-realistic drumming experience. We use a local and adaptive search to detect the effective points of the drum sticks, which ensures robustness to background clutter and reduces the computational burden. We have developed a working demo and evaluated its performance by comparing with the output signal of an electronic drum pad. We observed that the timing errors have an average of -8.4 ms and a standard deviation of 5.4 ms in a real drumming experiment consisting of 121 hits. ©2010 IEEE. © 2011 Elsevier B.V., All rights reserved.Publication Metadata only Inter-hemispheric atrophy better correlates with expert ratings than hemispheric cortical atrophy, İnterhemi̇sferi̇k atrofi̇ ölçümleri̇ hemi̇sferi̇k korti̇kal atrofi̇ ölçümleri̇ i̇le karşilaştirildiǧinda uzman derecelendi̇ rmesi̇ i̇le daha uyumludur(2012) Başkaya, Osman; Kandemir, Melek; Tepe, Muzaffer Savaş; Acar, M.; Unal, Gozde Bozkurt; Yalçıner, Zehra Betül; Ünay, Devrim; Başkaya, Osman, Bahçeşehir Üniversitesi, Istanbul, Turkey; Kandemir, Melek,; Tepe, Muzaffer Savaş, Radyoloji Departmani, Istanbul, Turkey; Acar, M., Radyoloji Departmani, Istanbul, Turkey; Unal, Gozde Bozkurt, Mühendislik ve Doǧa Bilimleri Fakültesi, Sabancı Üniversitesi, Tuzla, Turkey; Yalçıner, Zehra Betül,; Ünay, Devrim, Bahçeşehir Üniversitesi, Istanbul, TurkeyBrain atrophy is one of the parameters considered by experts for rating dementia from neuro-imaging findings. Research efforts have focused on measuring brain atrophy from images through experts' visual assessment or computer-based approaches. However, agreement between the visual assessment and computer-based measurement of atrophy is not yet investigated. Accordingly, this paper presents an automated method for cerebral atrophy assessment from cross-sectional MRI through hemispheric volume loss. For this purpose, the proposed method quantifies inter-hemispheric distance, and the distance between the cranium and the brain parenchyma, separately. Discriminative power of the proposed method is evaluated on two datasets with experts' visual gradings: Yue et al.'s data and a newly created reference dataset. Results show that inter-hemispheric atrophy better correlates with visual grades, and inconsistencies at the skull-stripping or brain tissue extraction steps can degrade the agreement between computer-based measurements and expert gradings. © 2012 IEEE. © 2013 Elsevier B.V., All rights reserved.Publication Metadata only Region growing on frangi vesselness values in 3-D CTA data, 3-BOYUTLU bt anjiyografi verilerinde frangi damarlik yöntemi üzerine bölge büyütme yaklasimi(2013) Oksuz, Ilkay; Ünay, Devrim; Kadipaşaoǧlu, Kâmuran A.; Oksuz, Ilkay, Bahçeşehir Üniversitesi, Istanbul, Turkey; Ünay, Devrim, Bahçeşehir Üniversitesi, Istanbul, Turkey; Kadipaşaoǧlu, Kâmuran A., Bahçeşehir Üniversitesi, Istanbul, TurkeyIn cardiac related diagnostic methods, the shape and curvature of coronary arteries is essential. Consequently, one of the most important requirements for Computer Aided Diagnosis (CAD) Systems is automated segmentation of vasculature. In this paper, we propose a new hybrid algorithm, which segment the coronary arterial tree in CTA images by merging methodologies-, namely, Region Growing and Frangi Approach. The algorithm first runs a region growing on Frangi vesselness values and subsequently optimizes the results with several threshold values. Comparison of the present results with optimal results of existing segmentation algorithms reveals that the proposed approach outperforms its predecessors. The diagnostic accuracy of the algorithm will next be validated on the segmentation of coronary arteries from real CT data. © 2013 IEEE. © 2013 Elsevier B.V., All rights reserved.Publication Metadata only Text mining in radiology reports, Radyoloji raporlarinda metin madenciligi(2013) Kocatekin, Tugberk; Ünay, Devrim; Kocatekin, Tugberk, Bahçeşehir Üniversitesi, Istanbul, Turkey; Ünay, Devrim, Bahçeşehir Üniversitesi, Istanbul, TurkeyText mining is a popular research topic with application areas ranging from security to media and marketing. More specifically, text mining has been applied in biomedical area for the categorization of radiology reports, which is a challenging problem due to their free-text and unstructured format. State-of-the-Art in radiology report mining has mostly focused on English text, while studies on Turkish reports are scarce. Accordingly, in this work we propose to employ text mining for categorization of Turkish radiology reports. We automatically remove header and footer of the reports, apply frequency analysis on the remaining report text, and perform categorization of reports to anatomical regions using pre-selected keywords. The accuracy of the proposed solution is measured as 84.3% over a 66-report test set. © 2013 IEEE. © 2013 Elsevier B.V., All rights reserved.Publication Metadata only Automated aortic supravalvular sinus detection in conventional computed tomography image, Bilgisayarli tomografi görüntülerinde otomatik aortik kapaküstü bölgesi tanimlama(2013) Ünay, Devrim; Harmankaya, İbrahim; Oksuz, Ilkay; Kadipaşaoǧlu, Kâmuran A.; Çubuk, Rahmi; Çelìk, Levent; Ünay, Devrim, Bahçeşehir Üniversitesi, Istanbul, Turkey; Harmankaya, İbrahim, Bahçeşehir Üniversitesi, Istanbul, Turkey; Oksuz, Ilkay, Bahçeşehir Üniversitesi, Istanbul, Turkey; Kadipaşaoǧlu, Kâmuran A., Bahçeşehir Üniversitesi, Istanbul, Turkey; Çubuk, Rahmi, Faculty of Medicine, T.C. Maltepe Universitesi, Istanbul, Turkey; Çelìk, Levent, Faculty of Medicine, T.C. Maltepe Universitesi, Istanbul, TurkeyValvular diseases are those where one or more of the cardiac valves are affected. Treatment of valvular diseases often involves replacement or restoration of the affected valve(s). In such a surgical procedure, the medical expert performing the procedure can largely benefit from a patient-specific and dynamic valvular model containing information complementary to the 2D/3D static images. To this end, in this study a novel automated supravalvular sinus detection method (to be used as a first step in aortic valve segmentation) on conventional contrast-enhanced ECG-gated multislice CT data and its evaluation on expert annotated 31 real cases are presented. Results demonstrate a highly accurate detection performance with average error rate inferior to 1.12 mm. © 2013 IEEE. © 2013 Elsevier B.V., All rights reserved.Publication Metadata only 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, TurkeyAnalysing 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.Publication Metadata only 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, TurkeyThe 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.Publication Metadata only 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, TurkeySegmentation 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.