{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:14:30Z","timestamp":1750220070116,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":29,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,12,8]],"date-time":"2022-12-08T00:00:00Z","timestamp":1670457600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001409","name":"Department of Science and Technology, Ministry of Science and Technology, India","doi-asserted-by":"publisher","award":["SR\/WOSA\/ET-153\/2017"],"award-info":[{"award-number":["SR\/WOSA\/ET-153\/2017"]}],"id":[{"id":"10.13039\/501100001409","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,12,8]]},"DOI":"10.1145\/3571600.3571632","type":"proceedings-article","created":{"date-parts":[[2023,5,12]],"date-time":"2023-05-12T22:17:26Z","timestamp":1683929846000},"page":"1-8","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Effect of Particle Image Velocimetry processing on CT Dicom images in a deep learning based pipeline for lung nodule segmentation\u2731"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2017-3067","authenticated-orcid":false,"given":"R Jenkin","family":"Suji","sequence":"first","affiliation":[{"name":"ABV Indian Institute of Information Technology and Management Gwalior, IN"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0720-2647","authenticated-orcid":false,"given":"W Wilfred","family":"Godfrey","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, ABV Indian Institute of Information Technology and Management Gwalior, IN"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0861-730X","authenticated-orcid":false,"family":"Dhar","sequence":"additional","affiliation":[{"name":"Department of Applied Sciences, ABV Indian Institute of Information Technology and Management Gwalior, India"}]}],"member":"320","published-online":{"date-parts":[[2023,5,12]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Echocardiographic Particle Image Velocimetry in Heart Diseases. In 2018 IEEE International Ultrasonics Symposium (IUS). IEEE, 1\u20131.","author":"Abe Haruhiko","year":"2018","unstructured":"Haruhiko Abe. 2018. Echocardiographic Particle Image Velocimetry in Heart Diseases. In 2018 IEEE International Ultrasonics Symposium (IUS). IEEE, 1\u20131."},{"volume-title":"Particle image velocimetry. Number\u00a030","author":"Adrian Lara","key":"e_1_3_2_1_2_1","unstructured":"Lara Adrian, Ronald\u00a0J Adrian, and Jerry Westerweel. 2011. Particle image velocimetry. Number\u00a030. Cambridge university press."},{"key":"e_1_3_2_1_3_1","volume-title":"The lung image database consortium (LIDC) and image database resource initiative (IDRI): a completed reference database of lung nodules on CT scans. Medical physics 38, 2","author":"G","year":"2011","unstructured":"Samuel\u00a0G Armato\u00a0III, Geoffrey McLennan, Luc Bidaut, Michael\u00a0F McNitt-Gray, Charles\u00a0R Meyer, Anthony\u00a0P Reeves, Binsheng Zhao, Denise\u00a0R Aberle, Claudia\u00a0I Henschke, Eric\u00a0A Hoffman, Ella\u00a0A Kazerooni, Heber MacMahon, Edwin J.\u00a0R van Beek, David Yankelevitz, Alberto\u00a0M Biancardi, Peyton\u00a0H Bland, Matthew\u00a0S Brown, Roger\u00a0M Engelmann, Gary\u00a0E Laderach, Daniel Max, Richard\u00a0C Pais, David P.-Y Qing, Rachael\u00a0Y Roberts, Amanda\u00a0R Smith, Adam Starkey, Poonam Batrah, Philip Caligiuri, Ali Farooqi, Gregory\u00a0W Gladish, C.\u00a0Matilda Jude, Reginald\u00a0F Munden, Iva Petkovska, Leslie\u00a0E Quint, Lawrence\u00a0H Schwartz, Baskaran Sundaram, Lori\u00a0E Dodd, Charles Fenimore, David Gur, Nicholas Petrick, John Freymann, Justin Kirby, Brian Hughes, Alessi\u00a0Vande Casteele, Sangeeta Gupte, Maha Sallamm, Michael\u00a0D Heath, Michael\u00a0H Kuhn, Ekta Dharaiya, Richard Burns, David\u00a0S Fryd, Marcos Salganicoff, Vikram Anand, Uri Shreter, Stephen Vastagh, Barbara\u00a0Y Croft, and Laurence\u00a0P Clarke. 2011. The lung image database consortium (LIDC) and image database resource initiative (IDRI): a completed reference database of lung nodules on CT scans. Medical physics 38, 2 (2011), 915\u2013931."},{"key":"e_1_3_2_1_4_1","volume-title":"Segnet: A deep convolutional encoder-decoder architecture for image segmentation","author":"Badrinarayanan Vijay","year":"2017","unstructured":"Vijay Badrinarayanan, Alex Kendall, and Roberto Cipolla. 2017. Segnet: A deep convolutional encoder-decoder architecture for image segmentation. IEEE transactions on pattern analysis and machine intelligence 39, 12(2017), 2481\u20132495."},{"key":"e_1_3_2_1_5_1","unstructured":"Ioana Barbu C\u00e9dric Herzet and Etienne M\u00e9min. 2011. Sparse models and pursuit algorithms for PIV tomography. In Forum on recent developments in Volume Reconstruction techniques applied to 3D fluid and solid mechanics."},{"key":"e_1_3_2_1_6_1","volume-title":"Lung nodule segmentation in chest computed tomography using a novel background estimation method. Quantitative imaging in medicine and surgery 6, 1","author":"Cavalcanti G","year":"2016","unstructured":"Pablo\u00a0G Cavalcanti, Shahram Shirani, Jacob Scharcanski, Crystal Fong, Jane Meng, Jane Castelli, and David Koff. 2016. Lung nodule segmentation in chest computed tomography using a novel background estimation method. Quantitative imaging in medicine and surgery 6, 1 (2016), 16."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.4103\/0256-4602.101306"},{"key":"e_1_3_2_1_9_1","volume-title":"Computer-aided detection (CADe) and diagnosis (CADx) system for lung cancer with likelihood of malignancy. Biomedical engineering online 15, 1","author":"Firmino Macedo","year":"2016","unstructured":"Macedo Firmino, Giovani Angelo, Higor Morais, Marcel\u00a0R Dantas, and Ricardo Valentim. 2016. Computer-aided detection (CADe) and diagnosis (CADx) system for lung cancer with likelihood of malignancy. Biomedical engineering online 15, 1 (2016), 2."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/ULTSYM.2016.7728440"},{"key":"e_1_3_2_1_11_1","volume-title":"Automatic detection of subsolid pulmonary nodules in thoracic computed tomography images. Medical image analysis 18, 2","author":"Jacobs Colin","year":"2014","unstructured":"Colin Jacobs, Eva\u00a0M van Rikxoort, Thorsten Twellmann, Ernst\u00a0Th Scholten, Pim\u00a0A de Jong, Jan-Martin Kuhnigk, Matthijs Oudkerk, Harry\u00a0J de Koning, Mathias Prokop, Cornelia Schaefer-Prokop, and Bram Van\u00a0Ginneken. 2014. Automatic detection of subsolid pulmonary nodules in thoracic computed tomography images. Medical image analysis 18, 2 (2014), 374\u2013384."},{"key":"e_1_3_2_1_12_1","volume-title":"Muhammad Zia\u00a0Ur Rehman, and Syed Irtiza\u00a0Ali Shah","author":"Javaid Muzzamil","year":"2016","unstructured":"Muzzamil Javaid, Moazzam Javid, Muhammad Zia\u00a0Ur Rehman, and Syed Irtiza\u00a0Ali Shah. 2016. A novel approach to CAD system for the detection of lung nodules in CT images. Computer methods and programs in biomedicine 135 (2016), 125\u2013139."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.3126\/jie.v7i1.2057"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-015-9801-9"},{"key":"e_1_3_2_1_16_1","unstructured":"Mahesh Nagargoje. 2017. An introduction to particle image velocimetry (PIV) technique."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"crossref","unstructured":"Syed\u00a0Muhammad Naqi Muhammad Sharif and Mussarat Yasmin. 2018. Multistage segmentation model and SVM-ensemble for precise lung nodule detection. International journal of computer assisted radiology and surgery 13 7(2018) 1083\u20131095.","DOI":"10.1007\/s11548-018-1715-9"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.178"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"crossref","unstructured":"Kraig\u00a0J Olejniczak. 2000. The Hartley transform. The transforms and applications handbook(2000) 281\u2013330.","DOI":"10.1201\/9781420036756.ch4"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics9010029"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_3_2_1_22_1","volume-title":"Refinement of lung nodule candidates based on local geometric shape analysis and Laplacian of Gaussian kernels. Computers in biology and medicine 54","author":"Saien Soudeh","year":"2014","unstructured":"Soudeh Saien, Abdol\u00a0Hamid Pilevar, and Hamid\u00a0Abrishami Moghaddam. 2014. Refinement of lung nodule candidates based on local geometric shape analysis and Laplacian of Gaussian kernels. Computers in biology and medicine 54 (2014), 188\u2013198."},{"key":"e_1_3_2_1_23_1","volume-title":"Automatic detection of large pulmonary solid nodules in thoracic CT images. Medical physics 42, 10","author":"Setio AA","year":"2015","unstructured":"Arnaud\u00a0AA Setio, Colin Jacobs, Jaap Gelderblom, and Bram van Ginneken. 2015. Automatic detection of large pulmonary solid nodules in thoracic CT images. Medical physics 42, 10 (2015), 5642\u20135653."},{"key":"e_1_3_2_1_24_1","volume-title":"Piergiorgio Cerello, Hao Chen, Qi Dou","author":"Arindra\u00a0Adiyoso Setio Arnaud","year":"2017","unstructured":"Arnaud Arindra\u00a0Adiyoso Setio, Alberto Traverso, Thomas De\u00a0Bel, Moira\u00a0SN Berens, Cas Van Den\u00a0Bogaard, Piergiorgio Cerello, Hao Chen, Qi Dou, Maria\u00a0Evelina Fantacci, Bram Geurts, 2017. Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge. Medical image analysis 42 (2017), 1\u201313."},{"key":"e_1_3_2_1_25_1","volume-title":"Fully automatic detection of lung nodules in CT images using a hybrid feature set. Medical physics 44, 7","author":"Shaukat Furqan","year":"2017","unstructured":"Furqan Shaukat, Gulistan Raja, Ali Gooya, and Alejandro\u00a0F Frangi. 2017. Fully automatic detection of lung nodules in CT images using a hybrid feature set. Medical physics 44, 7 (2017), 3615\u20133629."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-020-00346-w"},{"key":"e_1_3_2_1_27_1","volume-title":"Proceedings 15th Int Symp on Applications of Laser Techniques to Fluid Mechanics.","author":"Tarashima Shuhei","year":"2010","unstructured":"Shuhei Tarashima, Manabu Tange, Satoshi Someya, Koji Okamoto, 2010. GPU accelerated direct cross-correlation PIV with window deformation. In Proceedings 15th Int Symp on Applications of Laser Techniques to Fluid Mechanics."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCIMAGING.119.008856"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2017.8037182"},{"key":"e_1_3_2_1_30_1","volume-title":"Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation. Medical image analysis 40","author":"Wang Shuo","year":"2017","unstructured":"Shuo Wang, Mu Zhou, Zaiyi Liu, Zhenyu Liu, Dongsheng Gu, Yali Zang, Di Dong, Olivier Gevaert, and Jie Tian. 2017. Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation. Medical image analysis 40 (2017), 172\u2013183."}],"event":{"name":"ICVGIP'22: Thirteenth Indian Conference on Computer Vision, Graphics and Image Processing","acronym":"ICVGIP'22","location":"Gandhinagar India"},"container-title":["Proceedings of the Thirteenth Indian Conference on Computer Vision, Graphics and Image Processing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3571600.3571632","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3571600.3571632","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:09:09Z","timestamp":1750183749000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3571600.3571632"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,8]]},"references-count":29,"alternative-id":["10.1145\/3571600.3571632","10.1145\/3571600"],"URL":"https:\/\/doi.org\/10.1145\/3571600.3571632","relation":{},"subject":[],"published":{"date-parts":[[2022,12,8]]},"assertion":[{"value":"2023-05-12","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}