{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,24]],"date-time":"2025-08-24T00:01:03Z","timestamp":1755993663951,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":39,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,9,22]],"date-time":"2023-09-22T00:00:00Z","timestamp":1695340800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,9,22]]},"DOI":"10.1145\/3632047.3632070","type":"proceedings-article","created":{"date-parts":[[2024,2,27]],"date-time":"2024-02-27T18:48:15Z","timestamp":1709059695000},"page":"149-156","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Hybrid Approach for Accurate Fiber Estimation in Brain Tissues: Mixture Model and Deep Learning Technique"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5238-5964","authenticated-orcid":false,"given":"Ashishi","family":"Puri","sequence":"first","affiliation":[{"name":"Department of Mathematics, Indian Institute of Technology Roorkee, India and Department of Mathematics, School of Engineering, University of Petroleum and Energy Studies (UPES), Bidholi campus, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7728-3668","authenticated-orcid":false,"given":"Sanjeev","family":"Kumar","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Indian Institute of Technology Roorkee, India"}]}],"member":"320","published-online":{"date-parts":[[2024,2,27]]},"reference":[{"volume-title":"Tutorial on diffusion tensor MRI using Matlab. Electronic Edition","author":"Barmpoutis Angelos","key":"e_1_3_2_1_1_1","unstructured":"Angelos Barmpoutis. 2010. Tutorial on diffusion tensor MRI using Matlab. Electronic Edition, University of Florida (2010)."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-02498-6_28"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0006-3495(94)80775-1"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.softx.2022.101030"},{"key":"e_1_3_2_1_5_1","volume-title":"Invariant generalized functions in homogeneous domains. Functional analysis and its applications 9, 1","author":"Gindikin G","year":"1975","unstructured":"Simon\u00a0G Gindikin. 1975. Invariant generalized functions in homogeneous domains. Functional analysis and its applications 9, 1 (1975), 50\u201352."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2021.118198"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.1079"},{"key":"e_1_3_2_1_8_1","series-title":"Series A. Mathematical and Physical Sciences 229, 1178","volume-title":"The non-central Wishart distribution. Proceedings of the Royal Society of London","author":"James Anthony\u00a0Trafford","year":"1955","unstructured":"Anthony\u00a0Trafford James. 1955. The non-central Wishart distribution. Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences 229, 1178 (1955), 364\u2013366."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-73273-0_32"},{"key":"e_1_3_2_1_10_1","volume-title":"A machine learning-based method for estimating the number and orientations of major fascicles in diffusion-weighted magnetic resonance imaging. Medical image analysis 72","author":"Karimi Davood","year":"2021","unstructured":"Davood Karimi, Lana Vasung, Camilo Jaimes, Fedel Machado-Rivas, Shadab Khan, Simon\u00a0K Warfield, and Ali Gholipour. 2021. A machine learning-based method for estimating the number and orientations of major fascicles in diffusion-weighted magnetic resonance imaging. Medical image analysis 72 (2021), 102129."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2021.118316"},{"volume-title":"Modeling, analysis, and visualization of anisotropy","author":"Koppers Simon","key":"e_1_3_2_1_12_1","unstructured":"Simon Koppers, Matthias Friedrichs, and Dorit Merhof. 2017. Reconstruction of diffusion anisotropies using 3D deep convolutional neural networks in diffusion imaging. In Modeling, analysis, and visualization of anisotropy. Springer, 393\u2013404."},{"key":"e_1_3_2_1_13_1","volume-title":"Proceedings des Workshops vom 12","author":"Koppers Simon","year":"2017","unstructured":"Simon Koppers, Christoph Haarburger, J\u00a0Christopher Edgar, and Dorit Merhof. 2017. Reliable estimation of the number of compartments in diffusion mri. In Bildverarbeitung f\u00fcr die Medizin 2017: Algorithmen-Systeme-Anwendungen. Proceedings des Workshops vom 12. bis 14. M\u00e4rz 2017 in Heidelberg. Springer, 203\u2013208."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-47157-0_7"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"crossref","unstructured":"Charles\u00a0L Lawson and Richard\u00a0J Hanson. 1995. Solving least squares problems. SIAM.","DOI":"10.1137\/1.9781611971217"},{"key":"e_1_3_2_1_16_1","volume-title":"A tutorial on non central Wishart distributions. Technical Paper","author":"Letac Guy","year":"2004","unstructured":"Guy Letac and H Massam. 2004. A tutorial on non central Wishart distributions. Technical Paper, Toulouse University (2004)."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1081\/STA-120017798"},{"key":"e_1_3_2_1_18_1","volume-title":"Fast learning of fiber orientation distribution function for MR tractography using convolutional neural network. Medical physics 46, 7","author":"Lin Zhichao","year":"2019","unstructured":"Zhichao Lin, Ting Gong, Kewen Wang, Zhiwei Li, Hongjian He, Qiqi Tong, Feng Yu, and Jianhui Zhong. 2019. Fast learning of fiber orientation distribution function for MR tractography using convolutional neural network. Medical physics 46, 7 (2019), 3101\u20133116."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuron.2006.08.012"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-842X.1988.tb00482.x"},{"key":"e_1_3_2_1_21_1","volume-title":"Proceedings of the DMFC MICCAI 2009 Workshop.","author":"Nedjati-Gilani Shahrum","year":"2009","unstructured":"Shahrum Nedjati-Gilani and Daniel\u00a0C Alexander. 2009. Models for fanning and bending sub-voxel structures in diffusion MRI. In Proceedings of the DMFC MICCAI 2009 Workshop."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nec.2010.12.004"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.57.4.632"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1214\/aop\/1176990455"},{"key":"e_1_3_2_1_25_1","volume-title":"An iterative algorithm for computing gradient directions for white matter fascicles detection in brain MRI. Physical and Engineering Sciences in Medicine","author":"Puri Ashishi","year":"2023","unstructured":"Ashishi Puri and Sanjeev Kumar. 2023. An iterative algorithm for computing gradient directions for white matter fascicles detection in brain MRI. Physical and Engineering Sciences in Medicine (2023), 1\u201314."},{"key":"e_1_3_2_1_26_1","volume-title":"An Enhanced Multi-Fiber Reconstruction Technique using Adaptive Gradient Directions coupled with MoNCW Model in Diffusion MRI. Journal of Magnetic Resonance","author":"Puri Ashishi","year":"2021","unstructured":"Ashishi Puri, Snehlata Shakya, and Sanjeev Kumar. 2021. An Enhanced Multi-Fiber Reconstruction Technique using Adaptive Gradient Directions coupled with MoNCW Model in Diffusion MRI. Journal of Magnetic Resonance (2021), 106931."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1136\/jnnp.69.4.528"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0022-510X(01)00690-6"},{"key":"e_1_3_2_1_29_1","volume-title":"Cognitive functions correlate with white matter architecture in a normal pediatric population: a diffusion tensor MRI study. Human brain mapping 26, 2","author":"Schmithorst J","year":"2005","unstructured":"Vincent\u00a0J Schmithorst, Marko Wilke, Bernard\u00a0J Dardzinski, and Scott\u00a0K Holland. 2005. Cognitive functions correlate with white matter architecture in a normal pediatric population: a diffusion tensor MRI study. Human brain mapping 26, 2 (2005), 139\u2013147."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33454-2_61"},{"volume-title":"Modeling, Analysis, and Visualization of Anisotropy","author":"Shakya Snehlata","key":"e_1_3_2_1_31_1","unstructured":"Snehlata Shakya, Nazre Batool, Evren \u00d6zarslan, and Hans Knutsson. 2017. Multi-fiber reconstruction using probabilistic mixture models for diffusion MRI examinations of the brain. In Modeling, Analysis, and Visualization of Anisotropy. Springer, 283\u2013308."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.2312\/vcbm.20171244"},{"key":"e_1_3_2_1_33_1","volume-title":"Application of magnetic resonance DTI technique in evaluating the effect of postoperative exercise rehabilitation. Journal of Healthcare Engineering 2022","author":"Sheng Jinping","year":"2022","unstructured":"Jinping Sheng, Rui Jiang, Feizhou Du, Yang Wang, and Xiao Zhang. 2022. Application of magnetic resonance DTI technique in evaluating the effect of postoperative exercise rehabilitation. Journal of Healthcare Engineering 2022 (2022)."},{"key":"e_1_3_2_1_34_1","unstructured":"David\u00a0S Tuch. 1999. High angular resolution diffusion imaging of the human brain. In ISMRM Vol.\u00a0321."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.10268"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0896-6273(03)00758-X"},{"key":"e_1_3_2_1_37_1","volume-title":"Proceedings of the 8th Annual Meeting of ISMRM, Denver. 82","author":"Wedeen VJ","year":"2000","unstructured":"VJ Wedeen, TG Reese, DS Tuch, MR Weigel, JG Dou, RM Weiskoff, and D Chessler. 2000. Mapping fiber orientation spectra in cerebral white matter with Fourier-transform diffusion MRI. In Proceedings of the 8th Annual Meeting of ISMRM, Denver. 82."},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10443-0_27"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-66182-7_66"}],"event":{"name":"ICBRA 2023: 2023 the 10th International Conference on Bioinformatics Research and Application","acronym":"ICBRA 2023","location":"Barcelona Spain"},"container-title":["Proceedings of the 2023 10th International Conference on Bioinformatics Research and Applications"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3632047.3632070","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3632047.3632070","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T23:56:55Z","timestamp":1755907015000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3632047.3632070"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,22]]},"references-count":39,"alternative-id":["10.1145\/3632047.3632070","10.1145\/3632047"],"URL":"https:\/\/doi.org\/10.1145\/3632047.3632070","relation":{},"subject":[],"published":{"date-parts":[[2023,9,22]]},"assertion":[{"value":"2024-02-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}