{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T18:47:21Z","timestamp":1767984441609,"version":"3.49.0"},"reference-count":14,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":2315,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/2.0\/uk\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,6,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Digital reconstruction of 3D neuron structures is an important step toward reverse engineering the wiring and functions of a brain. However, despite a number of existing studies, this task is still challenging, especially when a 3D microscopic image has low single-to-noise ratio and discontinued segments of neurite patterns.<\/jats:p>\n               <jats:p>Results: We developed a graph-augmented deformable model (GD) to reconstruct (trace) the 3D structure of a neuron when it has a broken structure and\/or fuzzy boundary. We formulated a variational problem using the geodesic shortest path, which is defined as a combination of Euclidean distance, exponent of inverse intensity of pixels along the path and closeness to local centers of image intensity distribution. We solved it in two steps. We first used a shortest path graph algorithm to guarantee that we find the global optimal solution of this step. Then we optimized a discrete deformable curve model to achieve visually more satisfactory reconstructions. Within our framework, it is also easy to define an optional prior curve that reflects the domain knowledge of a user. We investigated the performance of our method using a number of challenging 3D neuronal image datasets of different model organisms including fruit fly, Caenorhabditis elegans, and mouse. In our experiments, the GD method outperformed several comparison methods in reconstruction accuracy, consistency, robustness and speed. We further used GD in two real applications, namely cataloging neurite morphology of fruit fly to build a 3D \u2018standard\u2019 digital neurite atlas, and estimating the synaptic bouton density along the axons for a mouse brain.<\/jats:p>\n               <jats:p>Availability: The software is provided as part of the V3D-Neuron 1.0 package freely available at http:\/\/penglab.janelia.org\/proj\/v3d<\/jats:p>\n               <jats:p>Contact: \u00a0pengh@janelia.hhmi.org<\/jats:p>","DOI":"10.1093\/bioinformatics\/btq212","type":"journal-article","created":{"date-parts":[[2010,6,7]],"date-time":"2010-06-07T07:28:13Z","timestamp":1275895693000},"page":"i38-i46","source":"Crossref","is-referenced-by-count":102,"title":["Automatic reconstruction of 3D neuron structures using a graph-augmented deformable model"],"prefix":"10.1093","volume":"26","author":[{"given":"Hanchuan","family":"Peng","sequence":"first","affiliation":[{"name":"Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA"}]},{"given":"Zongcai","family":"Ruan","sequence":"additional","affiliation":[{"name":"Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA"}]},{"given":"Deniz","family":"Atasoy","sequence":"additional","affiliation":[{"name":"Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA"}]},{"given":"Scott","family":"Sternson","sequence":"additional","affiliation":[{"name":"Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA"}]}],"member":"286","published-online":{"date-parts":[[2010,6,1]]},"reference":[{"key":"2023012508081600900_B1","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1109\/TITB.2002.1006304","article-title":"Rapid automated three-dimensional tracing of neurons from confocal image stacks","volume":"6","author":"Al-Kofahi","year":"2002","journal-title":"IEEE Trans. Inform. Technol. Biomedicine"},{"key":"2023012508081600900_B2","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1109\/TITB.2003.816564","article-title":"Median-based robust algorithms for tracing neurons from noisy confocal microscope images","volume":"7","author":"Al-Kofahi","year":"2003","journal-title":"IEEE Trans. Inform. Technol. Biomedicine"},{"key":"2023012508081600900_B3","doi-asserted-by":"crossref","first-page":"669","DOI":"10.1038\/nature01205","article-title":"The mechanosensory protein MEC-6 is a subunit of the C. elegans touch-cell degenerin channel","volume":"420","author":"Chelur","year":"2002","journal-title":"Nature"},{"key":"2023012508081600900_B4","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1007\/BF01386390","article-title":"A note on two problems in connexion with graphs","volume":"1","author":"Dijkstra","year":"1959","journal-title":"Numerische Mathematik"},{"key":"2023012508081600900_B5","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1002\/cyto.a.20022","article-title":"Design and validation of a tool for neurite tracing and analysis in fluorescence microscopy images","volume":"58A","author":"Meijering","year":"2004","journal-title":"Cytometry"},{"key":"2023012508081600900_B6","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1093\/bioinformatics\/btm569","article-title":"Straightening Caenorhabditis elegans images","volume":"24","author":"Peng","year":"2008","journal-title":"Bioinformatics"},{"key":"2023012508081600900_B7","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1038\/nbt.1612","article-title":"V3D enables real-time 3D visualization and quantitative analysis of large-scale biological image data sets","volume":"28","author":"Peng","year":"2010","journal-title":"Nat. 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Intell."},{"key":"2023012508081600900_B9","volume-title":"Grand Challenges for Engineering.","author":"Perry","year":"2008"},{"key":"2023012508081600900_B10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s12021-008-9043-9","article-title":"The central role of neuroinformatics in the national academy of engineering's grandest challenge: reverse engineer the brain","volume":"7","author":"Roysam","year":"2009","journal-title":"Neuroinformatics"},{"key":"2023012508081600900_B11","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1016\/j.neuroscience.2005.05.053","article-title":"New Techniques for imaging, digitization and analysis of three-dimensional neural morphology on multiple scales","volume":"136","author":"Wearne","year":"2005","journal-title":"Neuroscience"},{"key":"2023012508081600900_B12","first-page":"1111","article-title":"Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation","volume":"11","author":"Zana","year":"2001","journal-title":"IEEE Trans. Med. Imaging"},{"key":"2023012508081600900_B13","doi-asserted-by":"crossref","first-page":"1502","DOI":"10.1016\/j.neuroimage.2007.01.014","article-title":"Automated neurite extraction using dynamic programming for high-throughput screening of neuron-based assays","volume":"35","author":"Zhang","year":"2007","journal-title":"NeuroImage"},{"key":"2023012508081600900_B14","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1007\/s11265-008-0179-5","article-title":"Detection of retinal blood vessels based on nonlinear projections source","volume":"55","author":"Zhang","year":"2009","journal-title":"J. Signal Process. Syst."}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/26\/12\/i38\/48857216\/bioinformatics_26_12_i38.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/26\/12\/i38\/48857216\/bioinformatics_26_12_i38.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T08:12:31Z","timestamp":1674634351000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/26\/12\/i38\/285842"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010,6,1]]},"references-count":14,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2010,6,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btq212","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2010,6,15]]},"published":{"date-parts":[[2010,6,1]]}}}