Publication: Automated dendritic spine tracking on 2-photon microscopic images, 2-Foton Mikroskopi Goriintiilerinde Otomatik Dendritik Diken Takibi
| dc.contributor.author | Kilic, Bike | |
| dc.contributor.author | Rada, Lavdie | |
| dc.contributor.author | Erdil, Ertunç | |
| dc.contributor.author | Argunşah, Ali Özgür | |
| dc.contributor.author | Çetin, Müjdat | |
| dc.contributor.author | Ünay, Devrim | |
| dc.contributor.institution | Kilic, Bike, Bahçeşehir Üniversitesi, Istanbul, Turkey | |
| dc.contributor.institution | Rada, Lavdie, Bahçeşehir Üniversitesi, Istanbul, Turkey | |
| dc.contributor.institution | Erdil, Ertunç, Sabancı Üniversitesi, Tuzla, Turkey | |
| dc.contributor.institution | Argunşah, Ali Özgür, Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal | |
| dc.contributor.institution | Çetin, Müjdat, Sabancı Üniversitesi, Tuzla, Turkey | |
| dc.contributor.institution | Ünay, Devrim, Bahçeşehir Üniversitesi, Istanbul, Turkey | |
| dc.date.accessioned | 2025-10-05T16:31:45Z | |
| dc.date.issued | 2015 | |
| dc.description.abstract | 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. | |
| dc.identifier.conferenceName | 2015 23rd Signal Processing and Communications Applications Conference, SIU 2015 | |
| dc.identifier.conferencePlace | Malatya, Inonu Universitesi | |
| dc.identifier.doi | 10.1109/SIU.2015.7130222 | |
| dc.identifier.endpage | 1876 | |
| dc.identifier.isbn | 9781467373869 | |
| dc.identifier.scopus | 2-s2.0-84939146000 | |
| dc.identifier.startpage | 1873 | |
| dc.identifier.uri | https://doi.org/10.1109/SIU.2015.7130222 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14719/12747 | |
| dc.language.iso | tr | |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | |
| dc.subject.authorkeywords | 2-photon Microscopy | |
| dc.subject.authorkeywords | Dendritic Spine Tracking | |
| dc.subject.authorkeywords | Image Registration | |
| dc.subject.authorkeywords | Sift Features | |
| dc.subject.authorkeywords | Spine Detection | |
| dc.subject.authorkeywords | Image Registration | |
| dc.subject.authorkeywords | Optical Properties | |
| dc.subject.authorkeywords | Automatic Tools | |
| dc.subject.authorkeywords | Combined Detections | |
| dc.subject.authorkeywords | Dendritic Spine | |
| dc.subject.authorkeywords | Dynamic Structure | |
| dc.subject.authorkeywords | Microscopic Image | |
| dc.subject.authorkeywords | Morphological Changes | |
| dc.subject.authorkeywords | Sift Feature | |
| dc.subject.authorkeywords | Spine Detections | |
| dc.subject.authorkeywords | Signal Processing | |
| dc.subject.indexkeywords | Image registration | |
| dc.subject.indexkeywords | Optical properties | |
| dc.subject.indexkeywords | Automatic tools | |
| dc.subject.indexkeywords | Combined detections | |
| dc.subject.indexkeywords | Dendritic spine | |
| dc.subject.indexkeywords | Dynamic structure | |
| dc.subject.indexkeywords | Microscopic image | |
| dc.subject.indexkeywords | Morphological changes | |
| dc.subject.indexkeywords | SIFT Feature | |
| dc.subject.indexkeywords | Spine detections | |
| dc.subject.indexkeywords | Signal processing | |
| dc.title | Automated dendritic spine tracking on 2-photon microscopic images, 2-Foton Mikroskopi Goriintiilerinde Otomatik Dendritik Diken Takibi | |
| dc.type | Conference Paper | |
| dcterms.references | Fan, Jing, An automated pipeline for dendrite spine detection and tracking of 3D optical microscopy neuron images of in vivo mouse models, Neuroinformatics, 7, 2, pp. 113-130, (2009), Koh, Ingrid Y., Automated 3D dendritic spine detection and analysis from two-photon microscopy, Proceedings of SPIE - The International Society for Optical Engineering, 4261, pp. 48-59, (2001), Li, Qing, A global spatial similarity optimization scheme to track large numbers of dendritic spines in time-lapse confocal microscopy, IEEE Transactions on Medical Imaging, 30, 3, pp. 632-641, (2011), Miccai 2006 Workshop, (2006), von Bohlen und Halbach, Oliver, Structure and function of dendritic spines within the hippocampus, Annals of Anatomy, 191, 6, pp. 518-531, (2009), Fischer, Maria, Rapid actin-based plasticity in dendritic spines, Neuron, 20, 5, pp. 847-854, (1998), Kasai, Haruo, Structural dynamics of dendritic spines in memory and cognition, Trends in Neurosciences, 33, 3, pp. 121-129, (2010), Son, Jeany, Morphological change tracking of dendritic spines based on structural features, Journal of Microscopy, 241, 3, pp. 261-272, (2011), Rada, Lavdie, Automatic dendritic spine detection using multiscale dot enhancement filters and SIFT features, pp. 26-30, (2014), Cheng, Jie, A novel computational approach for automatic dendrite spines detection in two-photon laser scan microscopy, Journal of Neuroscience Methods, 165, 1, pp. 122-134, (2007) | |
| dspace.entity.type | Publication | |
| local.indexed.at | Scopus | |
| person.identifier.scopus-author-id | 56779763900 | |
| person.identifier.scopus-author-id | 55268679000 | |
| person.identifier.scopus-author-id | 36489496900 | |
| person.identifier.scopus-author-id | 24723512300 | |
| person.identifier.scopus-author-id | 35561229800 | |
| person.identifier.scopus-author-id | 55922238900 |
