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Sarthak Pati
Sarthak Pati
Indiana University; Technical University of Munich
Verified email at iu.edu - Homepage
Title
Cited by
Cited by
Year
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
23502020
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
10012020
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
4632021
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
1772018
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
1192022
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
1152016
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
1132020
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
1052021
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
732020
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
642021
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
642020
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
64*2016
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
612020
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
602018
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
502022
Standardised convolutional filtering for radiomics
A Depeursinge, V Andrearczyk, P Whybra, J van Griethuysen, H Müller, ...
arXiv preprint arXiv:2006.05470, 2020
432020
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
402023
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
392020
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
352022
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
302020
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