| Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge G Litjens, R Toth, W Van De Ven, C Hoeks, S Kerkstra, B Van Ginneken, ... Medical image analysis 18 (2), 359-373, 2014 | 767 | 2014 |
| Radiomics and radiogenomics in lung cancer: a review for the clinician R Thawani, M McLane, N Beig, S Ghose, P Prasanna, V Velcheti, ... Lung cancer 115, 34-41, 2018 | 455 | 2018 |
| A survey of prostate segmentation methodologies in ultrasound, magnetic resonance and computed tomography images S Ghose, A Oliver, R Martí, X Lladó, JC Vilanova, J Freixenet, J Mitra, ... Computer methods and programs in biomedicine 108 (1), 262-287, 2012 | 256 | 2012 |
| Automatic substitute computed tomography generation and contouring for magnetic resonance imaging (MRI)-alone external beam radiation therapy from standard MRI sequences JA Dowling, J Sun, P Pichler, D Rivest-Hénault, S Ghose, H Richardson, ... International Journal of Radiation Oncology* Biology* Physics 93 (5), 1144-1153, 2015 | 173 | 2015 |
| Lesion segmentation from multimodal MRI using random forest following ischemic stroke J Mitra, P Bourgeat, J Fripp, S Ghose, S Rose, O Salvado, A Connelly, ... NeuroImage 98, 324-335, 2014 | 159 | 2014 |
| Radiomic features from pretreatment biparametric MRI predict prostate cancer biochemical recurrence: preliminary findings R Shiradkar, S Ghose, I Jambor, P Taimen, O Ettala, AS Purysko, ... Journal of Magnetic Resonance Imaging 48 (6), 1626-1636, 2018 | 140 | 2018 |
| Radiomic features on MRI enable risk categorization of prostate cancer patients on active surveillance: Preliminary findings A Algohary, S Viswanath, R Shiradkar, S Ghose, S Pahwa, D Moses, ... Journal of Magnetic Resonance Imaging 48 (3), 818-828, 2018 | 122 | 2018 |
| A supervised learning framework of statistical shape and probability priors for automatic prostate segmentation in ultrasound images S Ghose, A Oliver, J Mitra, R Martí, X Lladó, J Freixenet, D Sidibé, ... Medical image analysis 17 (6), 587-600, 2013 | 73 | 2013 |
| Statistical machine learning to identify traumatic brain injury (TBI) from structural disconnections of white matter networks J Mitra, K Shen, S Ghose, P Bourgeat, J Fripp, O Salvado, K Pannek, ... Neuroimage 129, 247-259, 2016 | 72 | 2016 |
| A review of segmentation and deformable registration methods applied to adaptive cervical cancer radiation therapy treatment planning S Ghose, L Holloway, K Lim, P Chan, J Veera, SK Vinod, G Liney, ... Artificial intelligence in medicine 64 (2), 75-87, 2015 | 72 | 2015 |
| A spline-based non-linear diffeomorphism for multimodal prostate registration J Mitra, Z Kato, R Martí, A Oliver, X Lladó, D Sidibé, S Ghose, JC Vilanova, ... Medical image analysis 16 (6), 1259-1279, 2012 | 61 | 2012 |
| MRI‐alone radiation therapy planning for prostate cancer: automatic fiducial marker detection S Ghose, J Mitra, D Rivest‐Hénault, A Fazlollahi, P Stanwell, P Pichler, ... Medical physics 43 (5), 2218-2228, 2016 | 49 | 2016 |
| Advances and prospects for the Human BioMolecular Atlas Program (HuBMAP) S Jain, L Pei, JM Spraggins, M Angelo, JP Carson, N Gehlenborg, F Ginty, ... Nature cell biology 25 (8), 1089-1100, 2023 | 47 | 2023 |
| A random forest based classification approach to prostate segmentation in MRI S Ghose, J Mitra, A Oliver, R Marti, X Lladó, J Freixenet, JC Vilanova, ... MICCAI Grand Challenge: Prostate MR Image Segmentation 2012, 125-128, 2012 | 42 | 2012 |
| Texture guided active appearance model propagation for prostate segmentation S Ghose, A Oliver, R Martí, X Lladó, J Freixenet, JC Vilanova, ... Prostate Cancer Imaging. Computer-Aided Diagnosis, Prognosis, and …, 2010 | 32 | 2010 |
| Multiple mean models of statistical shape and probability priors for automatic prostate segmentation S Ghose, A Oliver, R Martí, X Lladó, J Freixenet, J Mitra, JC Vilanova, ... Prostate Cancer Imaging. Image Analysis and Image-Guided Interventions …, 2011 | 26 | 2011 |
| Mass effect deformation heterogeneity (MEDH) on gadolinium-contrast T1-weighted MRI is associated with decreased survival in patients with right cerebral hemisphere … P Prasanna, J Mitra, N Beig, A Nayate, J Patel, S Ghose, R Thawani, ... Scientific reports 9 (1), 1145, 2019 | 25 | 2019 |
| A new machine learning approach for predicting likelihood of recurrence following ablation for atrial fibrillation from CT T Atta-Fosu, M LaBarbera, S Ghose, P Schoenhagen, W Saliba, PJ Tchou, ... BMC Medical Imaging 21, 1-12, 2021 | 24 | 2021 |
| Prostate segmentation with texture enhanced active appearance model S Ghose, A Oliver, R Martí, X Lladó, J Freixenet, JC Vilanova, ... 2010 Sixth International Conference on Signal-Image Technology and Internet …, 2010 | 24 | 2010 |
| Statistical shape and texture model of quadrature phase information for prostate segmentation S Ghose, A Oliver, R Martí, X Lladó, J Freixenet, J Mitra, JC Vilanova, ... International Journal of Computer Assisted Radiology and Surgery 7, 43-55, 2012 | 23 | 2012 |
Jhimli MitraPrincipal Scientist - Computer Vision, GE HealthCare Technology & Innovation Center在 ge.com 的电子邮件经过验证
