| 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 | 2315 | 2018 |
| 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 | 92 | 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 | 82 | 2020 |
| Deep learning radiomics algorithm for gliomas (drag) model: a novel approach using 3d unet based deep convolutional neural network for predicting survival in gliomas U Baid, S Talbar, S Rane, S Gupta, MH Thakur, A Moiyadi, S Thakur, ... Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2019 | 71 | 2019 |
| 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 | 62 | 2023 |
| Systematic evaluation of image tiling adverse effects on deep learning semantic segmentation GA Reina, R Panchumarthy, SP Thakur, A Bastidas, S Bakas Frontiers in neuroscience 14, 65, 2020 | 51 | 2020 |
| Brain tumor segmentation based on 3D residual U-Net M Bhalerao, S Thakur International MICCAI brainlesion workshop, 218-225, 2019 | 44 | 2019 |
| Reproducibility analysis of multi‐institutional paired expert annotations and radiomic features of the Ivy Glioblastoma Atlas Project (Ivy GAP) dataset S Pati, R Verma, H Akbari, M Bilello, VB Hill, C Sako, R Correa, N Beig, ... Medical physics 47 (12), 6039-6052, 2020 | 36 | 2020 |
| The federated tumor segmentation (FeTS) tool: an open-source solution to further solid tumor research S Pati, U Baid, B Edwards, MJ Sheller, P Foley, GA Reina, S Thakur, ... Physics in Medicine & Biology 67 (20), 204002, 2022 | 33 | 2022 |
| Skull-stripping of glioblastoma MRI scans using 3D deep learning SP Thakur, J Doshi, S Pati, SM Ha, C Sako, S Talbar, U Kulkarni, ... International MICCAI Brainlesion Workshop, 57-68, 2019 | 27 | 2019 |
| Federated learning for the classification of tumor infiltrating lymphocytes U Baid, S Pati, TM Kurc, R Gupta, E Bremer, S Abousamra, SP Thakur, ... arXiv preprint arXiv:2203.16622, 2022 | 21 | 2022 |
| Expert tumor annotations and radiomics for locally advanced breast cancer in DCE-MRI for ACRIN 6657/I-SPY1 R Chitalia, S Pati, M Bhalerao, SP Thakur, N Jahani, V Belenky, ... Scientific data 9 (1), 440, 2022 | 17 | 2022 |
| The federated tumor segmentation (fets) initiative: The first real-world large-scale data-private collaboration focusing on neuro-oncology U Baid, S Pati, S Thakur, B Edwards, M Sheller, J Martin, S Bakas Neuro-oncology 23, 135-135, 2021 | 10 | 2021 |
| GBM segmentation with 3D U-Net and survival prediction with radiomics U Baid, A Mahajan, S Talbar, S Rane, S Thakur, A Moiyadi, M Thakur, ... Pre-conference proceedings of the 7th medical image computing and computer …, 2018 | 10 | 2018 |
| Estimating glioblastoma biophysical growth parameters using deep learning regression S Pati, V Sharma, H Aslam, SP Thakur, H Akbari, A Mang, S Subramanian, ... Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2021 | 9 | 2021 |
| Optimization of deep learning based brain extraction in mri for low resource environments SP Thakur, S Pati, R Panchumarthy, D Karkada, J Wu, D Kurtaev, C Sako, ... International MICCAI Brainlesion Workshop, 151-167, 2021 | 8 | 2021 |
| Clinically Deployed Computational Assessment of Multiple Sclerosis Lesions SP Thakur, M Schindler, M Bilello, S Bakas Frontiers in Medicine, 639, 2022 | 7 | 2022 |
| Pose estimation for distracted driver detection using deep convolutional neural networks S Thakur, B Baheti, S Gajre, S Talbar Computer Vision Applications: Third Workshop, WCVA 2018, Held in Conjunction …, 2019 | 4 | 2019 |
| BraTS-Path Challenge: Assessing Heterogeneous Histopathologic Brain Tumor Sub-regions S Bakas, SP Thakur, S Faghani, M Moassefi, U Baid, V Chung, S Pati, ... arXiv preprint arXiv:2405.10871, 2024 | 2 | 2024 |
| NIMG-25. OPTIMIZATION OF ARTIFICIAL INTELLIGENCE ALGORITHMS FOR LOW-RESOURCE/CLINICAL ENVIRONMENTS: FOCUS ON CLINICALLY-RELEVANT GLIOMA REGION DELINEATION B Baheti, S Thakur, S Pati, D Karkada, R Panchumarthy, J Wu, S Mohan, ... Neuro-Oncology 24 (Suppl 7), vii167, 2022 | 2 | 2022 |
Spyridon BakasAssociate Professor, Indiana University. - Director, Division of Computational PathologyVerified email at iu.edu
