| The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping A Zwanenburg, M Vallières, MA Abdalah, HJWL Aerts, V Andrearczyk, ... Radiology 295 (2), 328-338, 2020 | 2617 | 2020 |
| Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data MJ Sheller, B Edwards, GA Reina, J Martin, S Pati, A Kotrotsou, ... Scientific reports 10 (1), 12598, 2020 | 1111 | 2020 |
| The rsna-asnr-miccai brats 2021 benchmark on brain tumor segmentation and radiogenomic classification U Baid, S Ghodasara, S Mohan, M Bilello, E Calabrese, E Colak, ... arXiv preprint arXiv:2107.02314, 2021 | 594 | 2021 |
| Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome C Davatzikos, S Rathore, S Bakas, S Pati, M Bergman, R Kalarot, ... Journal of medical imaging 5 (1), 011018-011018, 2018 | 199 | 2018 |
| 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), 1-17, 2022 | 163 | 2022 |
| ANHIR: automatic non-rigid histological image registration challenge J Borovec, J Kybic, I Arganda-Carreras, DV Sorokin, G Bueno, ... IEEE transactions on medical imaging 39 (10), 3042-3052, 2020 | 125 | 2020 |
| OpenFL: An open-source framework for Federated Learning GA Reina, A Gruzdev, P Foley, O Perepelkina, M Sharma, I Davidyuk, ... arXiv preprint arXiv:2105.06413, 2021 | 120 | 2021 |
| GLISTRboost: combining multimodal MRI segmentation, registration, and biophysical tumor growth modeling with gradient boosting machines for glioma segmentation S Bakas, K Zeng, A Sotiras, S Rathore, H Akbari, B Gaonkar, M Rozycki, ... Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2016 | 114 | 2016 |
| The federated tumor segmentation (fets) challenge S Pati, U Baid, M Zenk, B Edwards, M Sheller, GA Reina, P Foley, ... arXiv preprint arXiv:2105.05874, 2021 | 81 | 2021 |
| Standardization in quantitative imaging: a multicenter comparison of radiomic features from different software packages on digital reference objects and patient data sets M McNitt-Gray, S Napel, A Jaggi, SA Mattonen, L Hadjiiski, M Muzi, ... Tomography 6 (2), 118-128, 2020 | 74 | 2020 |
| Brain extraction on MRI scans in presence of diffuse glioma: Multi-institutional performance evaluation of deep learning methods and robust modality-agnostic training S Thakur, J Doshi, S Pati, S Rathore, C Sako, M Bilello, SM Ha, G Shukla, ... Neuroimage 220, 117081, 2020 | 72 | 2020 |
| The cancer imaging phenomics toolkit (CaPTk): technical overview S Pati, A Singh, S Rathore, A Gastounioti, M Bergman, P Ngo, SM Ha, ... Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2020 | 71 | 2020 |
| OpenFL: The Open Federated Learning library P Foley, MJ Sheller, B Edwards, S Pati, W Riviera, M Sharma, PN Moorthy, ... Physics in Medicine & Biology 67 (21), 214001, 2022 | 68 | 2022 |
| Segmentation of gliomas in pre-operative and post-operative multimodal magnetic resonance imaging volumes based on a hybrid generative-discriminative framework K Zeng, S Bakas, A Sotiras, H Akbari, M Rozycki, S Rathore, S Pati, ... Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2016 | 67* | 2016 |
| Brain cancer imaging phenomics toolkit (brain-CaPTk): an interactive platform for quantitative analysis of glioblastoma S Rathore, S Bakas, S Pati, H Akbari, R Kalarot, P Sridharan, M Rozycki, ... Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2018 | 61 | 2018 |
| The rsna-asnr-miccai brats 2021 benchmark on brain tumor segmentation and radiogenomic classification. arXiv 2021 U Baid, S Ghodasara, S Mohan, M Bilello, E Calabrese, E Colak, ... arXiv preprint arXiv:2107.02314, 2021 | 57 | 2021 |
| The University of Pennsylvania glioblastoma (UPenn-GBM) cohort: advanced MRI, clinical, genomics, & radiomics S Bakas, C Sako, H Akbari, M Bilello, A Sotiras, G Shukla, JD Rudie, ... Scientific data 9 (1), 453, 2022 | 53 | 2022 |
| GaNDLF: the generally nuanced deep learning framework for scalable end-to-end clinical workflows S Pati, SP Thakur, İE Hamamcı, U Baid, B Baheti, M Bhalerao, O Güley, ... Communications Engineering 2 (1), 23, 2023 | 50 | 2023 |
| Standardised convolutional filtering for radiomics A Depeursinge, V Andrearczyk, P Whybra, J van Griethuysen, H Müller, ... arXiv preprint arXiv:2006.05470, 2020 | 45 | 2020 |
| Federated benchmarking of medical artificial intelligence with MedPerf A Karargyris, R Umeton, MJ Sheller, A Aristizabal, J George, A Wuest, ... Nature machine intelligence 5 (7), 799-810, 2023 | 40 | 2023 |
Spyridon BakasAssociate Professor, Indiana University. - Director, Division of Computational PathologyVerified email at iu.edu
