Event Abstract Back to Event Receptive Fields for EM Image Alignment and Neural Reconstruction Seymour Knowles-Barley1* 1 University of Edinburgh, United Kingdom A system utilising learnt receptive fields is proposed to improve transmission electron microscopy (TEM) image alignment and provide partial 3D reconstructions of neural tissue.Serial section TEM can produce very high resolution reconstructions of neural morphology, including synaptic detail and in some cases protein localisation. Alignment and reconstruction of 2D TEM images is currently performed manually or semi-automatically, with the aid of computer software, to generate a 3D model of the imaged neural circuitry. In some cases approximate alignment can be achieved automatically but high quality circuit reconstructions still require many hours of manual annotation.In this system 2D receptive fields, similar to those found in biological vision systems, are learnt from TEM data using supervised learning techniques. These receptive fields are applied to TEM images to automatically annotate neuronal membrane, synaptic connections, and organelles such as mitochondria. Objects recognised by the system can be used to improve alignment of serial images and produce partial 3D reconstructions as a starting point for further manual annotation. Conference: Neuroinformatics 2009, Pilsen, Czechia, 6 Sep - 8 Sep, 2009. Presentation Type: Oral Presentation Topic: Neuroimaging Citation: Knowles-Barley S (2019). Receptive Fields for EM Image Alignment and Neural Reconstruction. Front. Neuroinform. Conference Abstract: Neuroinformatics 2009. doi: 10.3389/conf.neuro.11.2009.08.033 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 21 May 2009; Published Online: 09 May 2019. * Correspondence: Seymour Knowles-Barley, University of Edinburgh, Edinburgh, United Kingdom, seymour.kb@ed.ac.uk Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Seymour Knowles-Barley Google Seymour Knowles-Barley Google Scholar Seymour Knowles-Barley PubMed Seymour Knowles-Barley Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.