{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:28:27Z","timestamp":1750220907047,"version":"3.41.0"},"publisher-location":"New York, New York, USA","reference-count":15,"publisher":"ACM Press","license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1145\/3354031.3354035","type":"proceedings-article","created":{"date-parts":[[2019,9,27]],"date-time":"2019-09-27T12:34:07Z","timestamp":1569587647000},"page":"93-97","source":"Crossref","is-referenced-by-count":1,"title":["Minimal Path based Particle Tracking in Low SNR Fluorescence Microscopy Images"],"prefix":"10.1145","author":[{"given":"Sheng","family":"Lu","sequence":"first","affiliation":[{"name":"School of Electronic Science and Engineering, Nanjing University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tong","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Electronic Science and Engineering, Nanjing University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fan","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Electronic Science and Engineering, Nanjing University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenglei","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Electronic Science and Engineering, Nanjing University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sidan","family":"Du","sequence":"additional","affiliation":[{"name":"School of Electronic Science and Engineering, Nanjing University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Electronic Science and Engineering, Nanjing University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","reference":[{"key":"key-10.1145\/3354031.3354035-1","doi-asserted-by":"crossref","unstructured":"Ben N. G. Giepmans, et al. 2006. The fluorescent toolbox for assessing protein location and function. Science 312, 5771 (Apr. 2006), 217--224. DOI: https:\/\/doi.org\/10.1126\/science.1124618","DOI":"10.1126\/science.1124618"},{"key":"key-10.1145\/3354031.3354035-2","doi-asserted-by":"crossref","unstructured":"Na Ji, et al. 2009. Advances in the speed and resolution of light microscopy. Curr. Opin. Neurobiol. 18, 6 (Dec. 2008), 605--616. DOI: https:\/\/doi.org\/10.1016\/j.conb.2009.03.009","DOI":"10.1016\/j.conb.2009.03.009"},{"key":"key-10.1145\/3354031.3354035-3","doi-asserted-by":"crossref","unstructured":"Lei Yang, et al. 2012. A New Framework for Particle Detection in Low-SNR Fluorescence Live-Cell Images and Its Application for Improved Particle Tracking. IEEE Trans. Bio-med. Eng. 59, 7 (Apr. 2012), 2040--2050. DOI: https:\/\/doi.org\/10.1109\/TBME.2012.2196798","DOI":"10.1109\/TBME.2012.2196798"},{"key":"key-10.1145\/3354031.3354035-4","doi-asserted-by":"crossref","unstructured":"Y. Chen, et al. 2018. Measure and model a 3-D space-variant PSF for fluorescence microscopy image deblurring. Opt. Express 26, 11 (May 2018), 14375--14391. DOI: https:\/\/doi.org\/10.1364\/OE.26.014375","DOI":"10.1364\/OE.26.014375"},{"key":"key-10.1145\/3354031.3354035-5","doi-asserted-by":"crossref","unstructured":"Liang Liang, et al. 2014. A novel multiple hypothesis based particle tracking method for clathrin mediated endocytosis analysis using fluorescence microscopy. IEEE Trans. Image Process. 23, 4 (Apr. 2014), 1844--1857. DOI: https:\/\/doi.org\/10.1109\/TIP.2014.2303633","DOI":"10.1109\/TIP.2014.2303633"},{"key":"key-10.1145\/3354031.3354035-6","doi-asserted-by":"crossref","unstructured":"S. Jiang, X. Zhou, T. Kirchhausen, and S. T. C. Wong. 2007. Detection of molecular particles in live cells via machine learning. Cytom. Part A 71, 8 (Apr. 2007), 563--575. DOI: https:\/\/doi.org\/10.1002\/cyto.a.20404","DOI":"10.1002\/cyto.a.20404"},{"key":"key-10.1145\/3354031.3354035-7","doi-asserted-by":"crossref","unstructured":"Chunmei Shi, et al. 2016. Micro-object motion tracking based on the probability hypothesis density particle tracker. J. Math. Biol. 72, 5 (Apr. 2016), 1225--1254. DOI: https:\/\/doi.org\/10.1007\/s00285-015-0909-9","DOI":"10.1007\/s00285-015-0909-9"},{"key":"key-10.1145\/3354031.3354035-8","doi-asserted-by":"crossref","unstructured":"Khuloud Jaqaman, et al. 2008. Robust single-particle tracking in live-cell time-lapse sequences. Nat. Methods 5, 8 (July 2008), 695--702. DOI: https:\/\/doi.org\/10.1038\/nmeth.1237","DOI":"10.1038\/nmeth.1237"},{"key":"key-10.1145\/3354031.3354035-9","doi-asserted-by":"crossref","unstructured":"R. Chatterjee, et al. 2013. Cell tracking in microscopic video using matching and linking of bipartite graphs. Comput. Meth. Prog. Bio. 112, 3 (Dec. 2013), 422--431. DOI: https:\/\/doi.org\/10.1016\/j.cmpb.2013.08.001","DOI":"10.1016\/j.cmpb.2013.08.001"},{"key":"key-10.1145\/3354031.3354035-10","doi-asserted-by":"crossref","unstructured":"Ihor Smal, et al. 2010. Quantitative Comparison of Spot Detection Methods in Fluorescence Microscopy. IEEE Trans. Med. Imaging 29, 2 (Feb. 2010), 282--301. DOI: https:\/\/doi.org\/10.1109\/TMI.2009.2025127","DOI":"10.1109\/TMI.2009.2025127"},{"key":"key-10.1145\/3354031.3354035-11","doi-asserted-by":"crossref","unstructured":"Thibault Lagache, et al. 2015. Using steerable wavelets and minimal paths to reconstruct automatically filaments in fluorescence imaging. In Proceedings of 2015 IEEE International Conference on Image Processing. IEEE, Québec City, Canada, 706--709. DOI: https:\/\/doi.org\/10.1109\/ICIP.2015.7350890","DOI":"10.1109\/ICIP.2015.7350890"},{"key":"key-10.1145\/3354031.3354035-12","doi-asserted-by":"crossref","unstructured":"S. Bonneau, M. Dahan, and L. D. Cohen. 2005. Single quantum dot tracking based on perceptual grouping using minimal paths in a spatiotemporal volume. IEEE Trans. Image Process. 14, 9 (Sept. 2005), 1384--1395. DOI: https:\/\/doi.org\/10.1109\/TIP.2005.852794","DOI":"10.1109\/TIP.2005.852794"},{"key":"key-10.1145\/3354031.3354035-13","doi-asserted-by":"crossref","unstructured":"S. Garrido, L. Moreno, J.V. Gómez. 2015. Motion Planning Using Fast Marching Squared Method. In: G. Carbone, F. Gomez-Bravo (eds.) Motion and Operation Planning of Robotic Systems. Mechanisms and Machine Science, vol 29. Springer, Cham. DOI: https:\/\/doi.org\/10.1007\/978-3-319-14705-5_8","DOI":"10.1007\/978-3-319-14705-5_8"},{"key":"key-10.1145\/3354031.3354035-14","doi-asserted-by":"crossref","unstructured":"Laurent D. Cohen, Ron Kimmel. 1997. Global minimum for active contour models: a minimal path approach. Int. J. Comput. Vision 24, 1 (Aug. 1997), 57--78. DOI: https:\/\/doi.org\/10.1023\/A:1007922224810","DOI":"10.1023\/A:1007922224810"},{"key":"key-10.1145\/3354031.3354035-15","doi-asserted-by":"crossref","unstructured":"Yang Chen, et al. 2015. Curve-like structure extraction using minimal path propagation with backtracking. IEEE Trans. Image Process. 25, 2 (Nov. 2015), 988--1003. DOI: https:\/\/doi.org\/10.1109\/TIP.2015.2496279","DOI":"10.1109\/TIP.2015.2496279"}],"event":{"number":"4","sponsor":["Graduate School of Library, Information, and Media Studies, University of Tsukuba, Japan","Sichuan University"],"acronym":"ICBIP '19","name":"the 2019 4th International Conference","start":{"date-parts":[[2019,8,13]]},"location":"Chengdu, China","end":{"date-parts":[[2019,8,15]]}},"container-title":["Proceedings of the 2019 4th International Conference on Biomedical Signal and Image Processing (ICBIP 2019)  - ICBIP '19"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3354031.3354035","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/dl.acm.org\/ft_gateway.cfm?id=3354035&ftid=2085635&dwn=1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:44:55Z","timestamp":1750203895000},"score":1,"resource":{"primary":{"URL":"http:\/\/dl.acm.org\/citation.cfm?doid=3354031.3354035"}},"subtitle":[],"proceedings-subject":"Biomedical Signal and Image Processing (ICBIP 2019)","short-title":[],"issued":{"date-parts":[[2019]]},"references-count":15,"URL":"https:\/\/doi.org\/10.1145\/3354031.3354035","relation":{},"subject":[],"published":{"date-parts":[[2019]]}}}