| Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018 | 2322 | 2018 |
| Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI NM Braman, M Etesami, P Prasanna, C Dubchuk, H Gilmore, P Tiwari, ... Breast Cancer Research 19, 1-14, 2017 | 615 | 2017 |
| Perinodular and intranodular radiomic features on lung CT images distinguish adenocarcinomas from granulomas N Beig, M Khorrami, M Alilou, P Prasanna, N Braman, M Orooji, S Rakshit, ... Radiology 290 (3), 783-792, 2019 | 317 | 2019 |
| Radiomic features from the peritumoral brain parenchyma on treatment-naive multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme … P Prasanna, J Patel, S Partovi, A Madabhushi, P Tiwari European radiology 27, 4188-4197, 2017 | 297 | 2017 |
| Federated learning enables big data for rare cancer boundary detection S Pati, U Baid, B Edwards, M Sheller, SH Wang, GA Reina, P Foley, ... Nature communications 13 (1), 7346, 2022 | 249 | 2022 |
| Co-occurrence of local anisotropic gradient orientations (CoLlAGe): a new radiomics descriptor P Prasanna, P Tiwari, A Madabhushi Scientific reports 6 (1), 1-14, 2016 | 173 | 2016 |
| Multi-kernel graph embedding for detection, Gleason grading of prostate cancer via MRI/MRS P Tiwari, J Kurhanewicz, A Madabhushi Medical image analysis 17 (2), 219-235, 2013 | 138 | 2013 |
| Computer-extracted texture features to distinguish cerebral radionecrosis from recurrent brain tumors on multiparametric MRI: a feasibility study P Tiwari, P Prasanna, L Wolansky, M Pinho, M Cohen, AP Nayate, ... American Journal of Neuroradiology 37 (12), 2231-2236, 2016 | 130 | 2016 |
| Radiogenomic analysis of hypoxia pathway is predictive of overall survival in Glioblastoma N Beig, J Patel, P Prasanna, V Hill, A Gupta, R Correa, K Bera, S Singh, ... Scientific reports 8 (1), 7, 2018 | 128 | 2018 |
| Radiogenomic-based survival risk stratification of tumor habitat on Gd-T1w MRI is associated with biological processes in glioblastoma N Beig, K Bera, P Prasanna, J Antunes, R Correa, S Singh, ... Clinical Cancer Research 26 (8), 1866-1876, 2020 | 112 | 2020 |
| Multimodal wavelet embedding representation for data combination (MaWERiC): integrating magnetic resonance imaging and spectroscopy for prostate cancer detection P Tiwari, S Viswanath, J Kurhanewicz, A Sridhar, A Madabhushi NMR in Biomedicine 25 (4), 607-619, 2012 | 100 | 2012 |
| Shape features of the lesion habitat to differentiate brain tumor progression from pseudoprogression on routine multiparametric MRI: a multisite study M Ismail, V Hill, V Statsevych, R Huang, P Prasanna, R Correa, G Singh, ... American Journal of Neuroradiology 39 (12), 2187-2193, 2018 | 88 | 2018 |
| Computer assisted diagnosis (CAD) of cancer using multi-functional, multi-modal in-vivo magnetic resonance spectroscopy (MRS) and imaging (MRI) MD Feldman, S Viswanath, P Tiwari, R Toth, A Madabhushi, ... US Patent 8,295,575, 2012 | 79 | 2012 |
| A hierarchical spectral clustering and nonlinear dimensionality reduction scheme for detection of prostate cancer from magnetic resonance spectroscopy (MRS) P Tiwari, M Rosen, A Madabhushi Medical physics 36 (9Part1), 3927-3939, 2009 | 77 | 2009 |
| Identifying the morphologic basis for radiomic features in distinguishing different Gleason grades of prostate cancer on MRI: Preliminary findings G Penzias, A Singanamalli, R Elliott, J Gollamudi, N Shih, M Feldman, ... PloS one 13 (8), e0200730, 2018 | 67 | 2018 |
| Introduction to radiomics and radiogenomics in neuro-oncology: implications and challenges N Beig, K Bera, P Tiwari Neuro-Oncology Advances 2 (Supplement_4), iv3-iv14, 2020 | 62 | 2020 |
| A magnetic resonance spectroscopy driven initialization scheme for active shape model based prostate segmentation R Toth, P Tiwari, M Rosen, G Reed, J Kurhanewicz, A Kalyanpur, ... Medical Image Analysis 15 (2), 214-225, 2011 | 61 | 2011 |
| MRQy—An open‐source tool for quality control of MR imaging data AR Sadri, A Janowczyk, R Zhou, R Verma, N Beig, J Antunes, ... Medical physics 47 (12), 6029-6038, 2020 | 60 | 2020 |
| Tumor habitat–derived radiomic features at pretreatment MRI that are prognostic for progression-free survival in glioblastoma are associated with key morphologic attributes at … R Verma, R Correa, VB Hill, V Statsevych, K Bera, N Beig, A Mahammedi, ... Radiology: Artificial Intelligence 2 (6), e190168, 2020 | 48 | 2020 |
| Semi supervised multi kernel (SeSMiK) graph embedding: identifying aggressive prostate cancer via magnetic resonance imaging and spectroscopy P Tiwari, J Kurhanewicz, M Rosen, A Madabhushi Medical Image Computing and Computer-Assisted Intervention–MICCAI 2010: 13th …, 2010 | 46 | 2010 |
Anant MadabhushiDepartment of Biomedical Engineering, Professor, Biomedical Engineering, Emory Univ & Georgia TechBestätigte E-Mail-Adresse bei emory.edu
