| Heterogeneous tumor-immune microenvironments among differentially growing metastases in an ovarian cancer patient A Jiménez-Sánchez, D Memon, S Pourpe, H Veeraraghavan, Y Li, ... Cell 170 (5), 927-938. e20, 2017 | 456 | 2017 |
| Haralick texture analysis of prostate MRI: utility for differentiating non-cancerous prostate from prostate cancer and differentiating prostate cancers with different Gleason … A Wibmer, H Hricak, T Gondo, K Matsumoto, H Veeraraghavan, D Fehr, ... European radiology 25, 2840-2850, 2015 | 453 | 2015 |
| Automatic classification of prostate cancer Gleason scores from multiparametric magnetic resonance images D Fehr, H Veeraraghavan, A Wibmer, T Gondo, K Matsumoto, HA Vargas, ... Proceedings of the National Academy of Sciences 112 (46), E6265-E6273, 2015 | 435 | 2015 |
| Vision 20/20: perspectives on automated image segmentation for radiotherapy G Sharp, KD Fritscher, V Pekar, M Peroni, N Shusharina, ... Medical physics 41 (5), 050902, 2014 | 406 | 2014 |
| A rectal cancer organoid platform to study individual responses to chemoradiation K Ganesh, C Wu, KP O’Rourke, BC Szeglin, Y Zheng, CEG Sauvé, ... Nature medicine 25 (10), 1607-1614, 2019 | 401 | 2019 |
| MR imaging of rectal cancer: radiomics analysis to assess treatment response after neoadjuvant therapy N Horvat, H Veeraraghavan, M Khan, I Blazic, J Zheng, M Capanu, E Sala, ... Radiology 287 (3), 833-843, 2018 | 323 | 2018 |
| Unravelling tumour heterogeneity using next-generation imaging: radiomics, radiogenomics, and habitat imaging E Sala, E Mema, Y Himoto, H Veeraraghavan, JD Brenton, A Snyder, ... Clinical radiology 72 (1), 3-10, 2017 | 323 | 2017 |
| Computer vision algorithms for intersection monitoring H Veeraraghavan, O Masoud, NP Papanikolopoulos IEEE Transactions on Intelligent Transportation Systems 4 (2), 78-89, 2003 | 315 | 2003 |
| Multiple resolution residually connected feature streams for automatic lung tumor segmentation from CT images J Jiang, YC Hu, CJ Liu, D Halpenny, MD Hellmann, JO Deasy, G Mageras, ... IEEE transactions on medical imaging 38 (1), 134-144, 2018 | 275 | 2018 |
| GBM volumetry using the 3D Slicer medical image computing platform J Egger, T Kapur, A Fedorov, S Pieper, JV Miller, H Veeraraghavan, ... Scientific reports 3 (1), 1364, 2013 | 270 | 2013 |
| Autosegmentation for thoracic radiation treatment planning: a grand challenge at AAPM 2017 J Yang, H Veeraraghavan, SG Armato III, K Farahani, JS Kirby, ... Medical physics 45 (10), 4568-4581, 2018 | 254 | 2018 |
| Tumor-aware, adversarial domain adaptation from CT to MRI for lung cancer segmentation J Jiang, YC Hu, N Tyagi, P Zhang, A Rimner, GS Mageras, JO Deasy, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 202 | 2018 |
| Differentiation of uterine leiomyosarcoma from atypical leiomyoma: diagnostic accuracy of qualitative MR imaging features and feasibility of texture analysis Y Lakhman, H Veeraraghavan, J Chaim, D Feier, DA Goldman, ... European radiology 27, 2903-2915, 2017 | 160 | 2017 |
| Breast cancer subtype intertumor heterogeneity: MRI‐based features predict results of a genomic assay EJ Sutton, JH Oh, BZ Dashevsky, H Veeraraghavan, AP Apte, SB Thakur, ... Journal of Magnetic Resonance Imaging 42 (5), 1398-1406, 2015 | 147 | 2015 |
| Breast cancer molecular subtype classifier that incorporates MRI features EJ Sutton, BZ Dashevsky, JH Oh, H Veeraraghavan, AP Apte, SB Thakur, ... Journal of Magnetic Resonance Imaging 44 (1), 122-129, 2016 | 145 | 2016 |
| Extension of CERR for computational radiomics: A comprehensive MATLAB platform for reproducible radiomics research AP Apte, A Iyer, M Crispin‐Ortuzar, R Pandya, LV Van Dijk, E Spezi, ... Medical physics 45 (8), 3713-3720, 2018 | 133 | 2018 |
| Multimodal data integration using machine learning improves risk stratification of high-grade serous ovarian cancer KM Boehm, EA Aherne, L Ellenson, I Nikolovski, M Alghamdi, ... Nature cancer 3 (6), 723-733, 2022 | 128 | 2022 |
| A novel representation of inter-site tumour heterogeneity from pre-treatment computed tomography textures classifies ovarian cancers by clinical outcome HA Vargas, H Veeraraghavan, M Micco, S Nougaret, Y Lakhman, ... European radiology 27, 3991-4001, 2017 | 107 | 2017 |
| Deep learning-based auto-segmentation of targets and organs-at-risk for magnetic resonance imaging only planning of prostate radiotherapy S Elguindi, MJ Zelefsky, J Jiang, H Veeraraghavan, JO Deasy, MA Hunt, ... Physics and imaging in radiation oncology 12, 80-86, 2019 | 106 | 2019 |
| Impact of image preprocessing on the scanner dependence of multi-parametric MRI radiomic features and covariate shift in multi-institutional glioblastoma datasets H Um, F Tixier, D Bermudez, JO Deasy, RJ Young, H Veeraraghavan Physics in Medicine & Biology 64 (16), 165011, 2019 | 95 | 2019 |
Joseph O. Deasy, PhDMemorial Sloan Kettering Cancer Center在 mskcc.org 的电子邮件经过验证
