Dmitry Goldgof

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Lawrence HallProfessor of Computer Science and Engineering, University of South FloridaAdresse e-mail validée de usf.edu
Robert GilliesChair of Cancer Physiology, H. Lee Moffitt Cancer CenterAdresse e-mail validée de moffitt.org
Rangachar KasturiDouglas W. Hood Professor Emeritus of Computer Science and Engineering, University of South FloridaAdresse e-mail validée de mail.usf.edu
Sudeep SarkarDistinguished University Professor, Computer Science and Engineering, University of South FloridaAdresse e-mail validée de usf.edu
Matthew B. Schabath, Ph.D.H. Lee Moffitt Cancer Center & Research InstituteAdresse e-mail validée de moffitt.org
Yoganand (Yoga) BalagurunathanMoffitt Cancer CenterAdresse e-mail validée de moffitt.org
peter moutonUniversity of South FloridaAdresse e-mail validée de disector.com
Kevin W. BowyerSchubmehl-Prein Family Professor of Computer Science and Engineering, University of Notre DameAdresse e-mail validée de nd.edu
Yu SunProfessor of Computer Science and Engineering, University of South FloridaAdresse e-mail validée de mail.usf.edu
Steven EschrichMoffitt Cancer CenterAdresse e-mail validée de moffitt.org
Matthew ShreveSenior Applied Scientist at AmazonAdresse e-mail validée de amazon.com
Adam HooverElectrical & Computer Engineering, Clemson UniversityAdresse e-mail validée de g.clemson.edu
Kurt KramerLarcos AquacultureAdresse e-mail validée de larcosaqua.com
Vasant ManoharOptumLabs - UnitedHealth R&DAdresse e-mail validée de optum.com
Chandra KambhamettuProfessor of Computer Science and Director of Video/Image Modeling and Synthesis (VIMS) Lab, University of DelawareAdresse e-mail validée de udel.edu
Mu ZhouStanford University; Rutgers UniversityAdresse e-mail validée de stanford.edu
Virendra KumarProfessor, Department of NMR, All India Institute of Medical SciencesAdresse e-mail validée de aiims.edu
Dmitry CherezovPhDAdresse e-mail validée de usf.edu
Hady Ahmady PhouladyCalifornia State University, SacramentoAdresse e-mail validée de csus.edu
Padmanabhan SoundararajanNielsenAdresse e-mail validée de nielsen.com

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Dmitry Goldgof

Distinguished Professor of Computer Science and Engineering, University of South Florida

Adresse e-mail validée de mail.usf.edu - Page d'accueil

Computer Science Biomedical AI Medical Image Analysis Image and Video Processing


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Radiomics: the process and the challenges V Kumar, Y Gu, S Basu, A Berglund, SA Eschrich, MB Schabath, K Forster, ... Magnetic resonance imaging 30 (9), 1234-1248, 2012	2374	2012
An experimental comparison of range image segmentation algorithms A Hoover, G Jean-Baptiste, X Jiang, PJ Flynn, H Bunke, DB Goldgof, ... IEEE transactions on pattern analysis and machine intelligence 18 (7), 673-689, 1996	1210	1996
Automatic tumor segmentation using knowledge-based techniques MC Clark, LO Hall, DB Goldgof, R Velthuizen, FR Murtagh, MS Silbiger IEEE transactions on medical imaging 17 (2), 187-201, 1998	735	1998
Framework for performance evaluation of face, text, and vehicle detection and tracking in video: Data, metrics, and protocol R Kasturi, D Goldgof, P Soundararajan, V Manohar, J Garofolo, R Bowers, ... IEEE transactions on pattern analysis and machine intelligence 31 (2), 319-336, 2008	682	2008
Intrinsic dependencies of CT radiomic features on voxel size and number of gray levels M Shafiq‐ul‐Hassan, GG Zhang, K Latifi, G Ullah, DC Hunt, ... Medical physics 44 (3), 1050-1062, 2017	605	2017
Understanding transit scenes: A survey on human behavior-recognition algorithms J Candamo, M Shreve, DB Goldgof, DB Sapper, R Kasturi IEEE transactions on intelligent transportation systems 11 (1), 206-224, 2009	444	2009
Automatic segmentation of non-enhancing brain tumors in magnetic resonance images LM Fletcher-Heath, LO Hall, DB Goldgof, FR Murtagh Artificial intelligence in medicine 21 (1-3), 43-63, 2001	411	2001
Radiomics in brain tumor: image assessment, quantitative feature descriptors, and machine-learning approaches M Zhou, J Scott, B Chaudhury, L Hall, D Goldgof, KW Yeom, M Iv, Y Ou, ... American Journal of Neuroradiology 39 (2), 208-216, 2018	404	2018
Reproducibility and prognosis of quantitative features extracted from CT images Y Balagurunathan, Y Gu, H Wang, V Kumar, O Grove, S Hawkins, J Kim, ... Translational oncology 7 (1), 72-87, 2014	356	2014
Active learning to recognize multiple types of plankton. T Luo, K Kramer, DB Goldgof, LO Hall, S Samson, A Remsen, T Hopkins, ... Journal of Machine Learning Research 6 (4), 2005	342	2005
Finding covid-19 from chest x-rays using deep learning on a small dataset LO Hall, R Paul, DB Goldgof, GM Goldgof arXiv preprint arXiv:2004.02060, 2020	318	2020
Predicting malignant nodules from screening CT scans S Hawkins, H Wang, Y Liu, A Garcia, O Stringfield, H Krewer, Q Li, ... Journal of Thoracic Oncology 11 (12), 2120-2128, 2016	318	2016
Fast accurate fuzzy clustering through data reduction S Eschrich, J Ke, LO Hall, DB Goldgof IEEE transactions on fuzzy systems 11 (2), 262-270, 2003	302	2003
MRI segmentation using fuzzy clustering techniques MC Clark, LO Hall, DB Goldgof, LP Clarke, RP Velthuizen, MS Silbiger IEEE Engineering in Medicine and Biology Magazine 13 (5), 730-742, 1994	300	1994
Test–retest reproducibility analysis of lung CT image features Y Balagurunathan, V Kumar, Y Gu, J Kim, H Wang, Y Liu, DB Goldgof, ... Journal of digital imaging 27, 805-823, 2014	295	2014
Macro-and micro-expression spotting in long videos using spatio-temporal strain M Shreve, S Godavarthy, D Goldgof, S Sarkar 2011 IEEE international conference on automatic face & gesture recognition …, 2011	285	2011
Knowledge-based classification and tissue labeling of MR images of human brain C Li, DB Goldgof, LO Hall IEEE transactions on Medical Imaging 12 (4), 740-750, 1993	275	1993
Comprehensive processing, display and analysis for in vivo MR spectroscopic imaging AA Maudsley, A Darkazanli, JR Alger, LO Hall, N Schuff, C Studholme, ... NMR in Biomedicine 19 (4), 492-503, 2006	260	2006
Deformable models in medical image analysis A Singh, D Terzopoulos, DB Goldgof IEEE Computer Society Press, 1998	224	1998
Deep feature transfer learning in combination with traditional features predicts survival among patients with lung adenocarcinoma R Paul, SH Hawkins, Y Balagurunathan, MB Schabath, RJ Gillies, LO Hall, ... Tomography 2 (4), 388, 2016	205	2016

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