| 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 | 2717 | 2020 |
| 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 | 1782 | 2018 |
| Epidermal growth factor receptor extracellular domain mutations in glioblastoma present opportunities for clinical imaging and therapeutic development ZA Binder, AH Thorne, S Bakas, EP Wileyto, M Bilello, H Akbari, ... Cancer cell 34 (1), 163-177. e7, 2018 | 160 | 2018 |
| Identifying the best machine learning algorithms for brain tumor segmentation S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... progression assessment, and overall survival prediction in the BRATS …, 2018 | 115 | 2018 |
| Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge. arXiv preprint … S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv, 1811 | 83 | 1811 |
| 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 | 66 | 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 | 62 | 2020 |
| 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 | 44 | 2022 |
| Cancer imaging phenomics via CaPTk: multi-institutional prediction of progression-free survival and pattern of recurrence in glioblastoma A Fathi Kazerooni, H Akbari, G Shukla, C Badve, JD Rudie, C Sako, ... JCO clinical cancer informatics 4, 234-244, 2020 | 39 | 2020 |
| Overall survival prediction in glioblastoma patients using structural magnetic resonance imaging (MRI): advanced radiomic features may compensate for lack of advanced MRI … S Bakas, G Shukla, H Akbari, G Erus, A Sotiras, S Rathore, C Sako, ... Journal of Medical Imaging 7 (3), 031505-031505, 2020 | 35 | 2020 |
| Multivalent binding of a ligand-coated particle: role of shape, size, and ligand heterogeneity M McKenzie, SM Ha, A Rammohan, R Radhakrishnan, N Ramakrishnan Biophysical Journal 114 (8), 1830-1846, 2018 | 34 | 2018 |
| 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 | 30 | 2020 |
| 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 | 24 | 2019 |
| Nimg-40. non-invasive in vivo signature of idh1 mutational status in high grade glioma, from clinically-acquired multi-parametric magnetic resonance imaging, using multivariate … S Bakas, S Rathore, ML Nasrallah, H Akbari, Z Binder, SM Ha, ... Neuro-oncology 20 (suppl_6), vi184-vi185, 2018 | 9 | 2018 |
| Integrative radiomic analysis for pre-surgical prognostic stratification of glioblastoma patients: from advanced to basic MRI protocols S Bakas, G Shukla, H Akbari, G Erus, A Sotiras, S Rathore, C Sako, ... Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and …, 2020 | 7 | 2020 |
| Neurodevelopmental patterns of early postnatal white matter maturation represent distinct underlying microstructure and histology A Nazeri, Ž Krsnik, I Kostović, SM Ha, J Kopić, D Alexopoulos, S Kaplan, ... Neuron 110 (23), 4015-4030. e4, 2022 | 6 | 2022 |
| Non-invasive determination of the O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation status in glioblastoma (GBM) using magnetic … S Rathore, S Bakas, MLP Nasrallah, SJ Bagley, H Akbari, SM Ha, ... Journal of Clinical Oncology 36 (15_suppl), 2051-2051, 2018 | 6 | 2018 |
| Nimg-45. multivariate pattern analysis of de novo glioblastoma patients offers in vivo evaluation of O6-methylguanine-DNA-methyltransferase (Mgmt) promoter methylation status … S Rathore, S Bakas, ML Nasrallah, H Akbari, S Bagley, SM Ha, ... Neuro-oncology 20 (Suppl 6), vi186, 2018 | 5 | 2018 |
| NIMG-40. Robust modality-agnostic skull-stripping in presence of diffuse glioma: a multi-institutional study S Thakur, J Doshi, S Min Ha, G Shukla, A Kotrotsou, S Talbar, U Kulkarni, ... Neuro-Oncology 21 (Supplement_6), vi170-vi170, 2019 | 2 | 2019 |
| Morphological versus functional network organization: A comparison between structural covariance networks and probabilistic functional modes P Lenzini, T Earnest, SM Ha, A Bani, A Sotiras, J Bijsterbosch International Workshop on Machine Learning in Clinical Neuroimaging, 163-172, 2023 | 1 | 2023 |
Spyridon BakasAssociate Professor, Indiana University. - Director, Division of Computational PathologyVerified email at iu.edu
