Publications
90 publications
Complete list sourced from papers.bib. Curated highlights on Google Scholar and ORCID.
2026
- An Unsupervised Brain Extraction Quality Control Approach for Efficient Neuro-Oncology Studies
Pati, Sarthak, Wagner, Stefan, Thakur, Siddhesh, Calabrese, Evan, Shinohara, Russell, Bakas, Spyridon
Journal of imaging informatics in medicineVol. 392026 - The 2024 Brain Tumor Segmentation Challenge Meningioma Radiotherapy (BraTS-MEN-RT) dataset
LaBella, Dominic, Schumacher, Katherine, Mix, Michael, Leu, Kevin, McBurney-Lin, Shan, et al.
Scientific Data2026
2025
- The Federated Tumor Segmentation (FeTS) Challenge 2024: Efficient and Robust Aggregation Methods
Linardos, Akis, Pati, Sarthak, Baid, Ujjwal, Edwards, Brandon, Foley, Patrick, et al.
Machine Learning for Biomedical ImagingVol. 32025 - IMG-69. FeTS 2.0: Federated learning sets benchmark in post-op GBM segmentation
LaBella, Dominic, Kassem, Hasan, Edwards, Brandon, Sheller, Micah, Pati, Sarthak, et al.
Neuro-OncologyVol. 272025 - IMG-121. BraTS-Pathology 2024: Insights and Future Directions Informed by the AI-RANO \& RANO-RGP Effort to Assess Glioblastoma Heterogeneity
Thakur, Siddhesh, Malec, Sylwia, Pitarc, Carla, Linardos, Akis, Innani, Shubham, et al.
Neuro-OncologyVol. 272025 - From screening to subtyping in a single glance
Pati, Sarthak
PatternsVol. 62025 - Optimization of deep learning models for inference in low resource environments
Thakur, Siddhesh, Pati, Sarthak, Wu, Junwen, Panchumarthy, Ravi, Karkada, Deepthi, et al.
Computers in Biology and MedicineVol. 1962025 - BrainLesion Suite: A Flexible and User-Friendly Framework for Modular Brain Lesion Image Analysis
Kofler, Florian, Rosier, Marcel, Astaraki, Mehdi, M{\"o
arXiv preprint arXiv:2507.090362025 - Towards fair decentralized benchmarking of healthcare AI algorithms with the Federated Tumor Segmentation (FeTS) challenge
Zenk, Marcel, Baid, Uday, Pati, Sarthak, others
Nature CommunicationsVol. 162025 - Informatics at the Frontier of Cancer Research
Noller, Kathleen, Botsis, Taxiarchis, Camara, Pablo G, Ciotti, Lauren, Cooper, Lee AD, et al.
Cancer Research2025 - BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023
Fathi Kazerooni, Anahita, Khalili, Nastaran, Liu, Xinyang, Haldar, Debanjan, Jiang, Zhifan, et al.
Machine Learning for Biomedical ImagingVol. 32025 - BraTS orchestrator: Democratizing and Disseminating state-of-the-art brain tumor image analysis
Kofler, Florian, Rosier, Marcel, Astaraki, Mehdi, Baid, Ujjwal, M{\"o
arXiv preprint arXiv:2506.138072025 - Inclusive, Differentially Private Federated Learning for Clinical Data
Parampottupadam, Santhosh, Co{\c{s
arXiv preprint arXiv:2505.221082025 - Analysis of the MICCAI Brain Tumor Segmentation--Metastases (BraTS-METS) 2025 Lighthouse Challenge: Brain Metastasis Segmentation on Pre-and Post-treatment MRI
Maleki, Nazanin, Amiruddin, Raisa, Moawad, Ahmed W, Yordanov, Nikolay, Gkampenis, Athanasios, et al.
arXiv preprint arXiv:2504.125272025 - Towards Reproducible, Stable, and Robust Machine Learning Research in Clinical Environments
Pati, Sarthak
2025 - Adapting to evolving MRI data: A transfer learning approach for Alzheimer's disease prediction
Turrisi, Rosanna, Pati, Sarthak, Pioggia, Giovanni, Tartarisco, Gennaro, Alzheimer's Disease Neuroimaging Initiative, others
NeuroImageVol. 3072025 - Collaborative evaluation for performance assessment of medical imaging applications
Kassem, Hasan, Singh, Akshita, Aristizabal, Alejandro, Bakas, Spyridon, Sheller, Micah, et al.
2025 - Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge
LaBella, Dominic, Baid, Ujjwal, Khanna, Omaditya, McBurney-Lin, Shan, McLean, Ryan, et al.
Machine Learning for Biomedical ImagingVol. 32025
2024
- Machine learning-based prognostic subgrouping of glioblastoma: A multicenter study
Akbari, Hamed, Bakas, Spyridon, Sako, Chiharu, Fathi Kazerooni, Anahita, Villanueva-Meyer, Javier, et al.
Neuro-Oncology2024 - Pan-Cancer Tumor Infiltrating Lymphocyte Detection based on Federated Learning
Baid, Ujjwal, Pati, Sarthak, Kurc, Tahsin M, Gupta, Rajarsi, Bremer, Erich, et al.
2024 - The image biomarker standardization initiative: standardized convolutional filters for reproducible radiomics and enhanced clinical insights
Whybra, Philip, Zwanenburg, Alex, Andrearczyk, Vincent, Schaer, Roger, Apte, Aditya P, et al.
RadiologyVol. 3102024 - BraTS-Path Challenge: Assessing Heterogeneous Histopathologic Brain Tumor Sub-regions
Bakas, Spyridon, Thakur, Siddhesh P, Faghani, Shahriar, Moassefi, Mana, Baid, Ujjwal, et al.
arXiv preprint arXiv:2405.108712024 - Brain tumor segmentation (brats) challenge 2024: Meningioma radiotherapy planning automated segmentation
LaBella, Dominic, Schumacher, Katherine, Mix, Michael, Leu, Kevin, McBurney-Lin, Shan, et al.
arXiv preprint arXiv:2405.183832024 - Advancing volumetric breast density segmentation: a deep learning approach with digital breast tomosynthesis
Doiphode, Nehal, Ahluwalia, Vinayak S, Mankowski, Walter C, Cohen, Eric A, Pati, Sarthak, et al.
Vol. 131742024 - Generatect: Text-conditional generation of 3d chest ct volumes
Hamamci, Ibrahim Ethem, Er, Sezgin, Sekuboyina, Anjany, Simsar, Enis, Tezcan, Alperen, et al.
2024 - Privacy preservation for federated learning in health care
Pati, Sarthak, Kumar, Sourav, Varma, Amokh, Edwards, Brandon, Lu, Charles, et al.
PatternsVol. 52024 - BraTS-PEDs: results of the multi-consortium international pediatric brain tumor segmentation challenge 2023
Kazerooni, Anahita Fathi, Khalili, Nastaran, Liu, Xinyang, Haldar, Debanjan, Jiang, Zhifan, et al.
arXiv preprint arXiv:2407.088552024 - Best practices to evaluate the impact of biomedical research software—metric collection beyond citations
Afiaz, Awan, Ivanov, Andrey A, Chamberlin, John, Hanauer, David, Savonen, Candace L, et al.
BioinformaticsVol. 402024 - GaNDLF-Synth: A Framework to Democratize Generative AI for (Bio) Medical Imaging
Pati, Sarthak, Mazurek, Szymon, Bakas, Spyridon
arXiv preprint arXiv:2410.001732024 - Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 1: review of current advancements
Villanueva-Meyer, Javier E, Bakas, Spyridon, Tiwari, Pallavi, Lupo, Janine M, Calabrese, Evan, et al.
The Lancet OncologyVol. 252024 - Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 2: recommendations for standardisation, validation, and good clinical practice
Bakas, Spyridon, Vollmuth, Philipp, Galldiks, Norbert, Booth, Thomas C, Aerts, Hugo JWL, et al.
The Lancet OncologyVol. 252024 - The Brain Tumor Segmentation-Metastases (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI
Moawad, Ahmed W, Janas, Anastasia, Baid, Ujjwal, Ramakrishnan, Divya, Saluja, Rachit, et al.
ArXiv2024 - TMIC-60. BRATS-PATH: ASSESSING HETEROGENEOUS HISTOPATHOLOGIC REGIONS IN GLIOBLASTOMA
Thakur, Siddhesh, Faghani, Shahriar, Moassefi, Mana, Baid, Ujjwal, Chung, Verena, et al.
Neuro-OncologyVol. 262024 - Volumetric Breast Density Estimation From Three-Dimensional Reconstructed Digital Breast Tomosynthesis Images Using Deep Learning
Ahluwalia, Vinayak S, Doiphode, Nehal, Mankowski, Walter C, Cohen, Eric A, Pati, Sarthak, et al.
JCO Clinical Cancer InformaticsVol. 82024
2023
- Robust image population based stain color normalization: How many reference slides are enough?
Agraz, Jose L, Grenko, Caleb M, Chen, Andrew A, Viaene, Angela N, Nasrallah, MacLean D, et al.
IEEE Open Journal of Engineering in Medicine and BiologyVol. 32023 - Why is the winner the best?
Eisenmann, Matthias, Reinke, Annika, Weru, Vivienn, Tizabi, Minu D, Isensee, Fabian, et al.
2023 - GaNDLF: the generally nuanced deep learning framework for scalable end-to-end clinical workflows
Pati, Sarthak, Thakur, Siddhesh P, Hamamc{\i
Communications EngineeringVol. 22023 - Generatect: Text-guided 3d chest ct generation
Hamamci, Ibrahim Ethem, Er, Sezgin, Simsar, Enis, Tezcan, Alperen, Simsek, Ayse Gulnihan, et al.
CoRR2023 - GenerateCT: Text-Conditional Generation of 3D Chest CT Volumes
Ethem Hamamci, Ibrahim, Er, Sezgin, Sekuboyina, Anjany, Simsar, Enis, Tezcan, Alperen, et al.
arXiv e-prints2023 - Dentex: An abnormal tooth detection with dental enumeration and diagnosis benchmark for panoramic x-rays
Hamamci, Ibrahim Ethem, Er, Sezgin, Simsar, Enis, Yuksel, Atif Emre, Gultekin, Sadullah, et al.
arXiv preprint arXiv:2305.191122023 - Evaluation of software impact designed for biomedical research: Are we measuring what's meaningful?
Afiaz, Awan, Ivanov, Andrey A, Chamberlin, John, Hanauer, David, Savonen, Candace L, et al.
ArXiv2023 - Federated benchmarking of medical artificial intelligence with MedPerf
Karargyris, Alexandros, Umeton, Renato, Sheller, Micah J, Aristizabal, Alejandro, George, Johnu, et al.
Nature machine intelligenceVol. 52023 - Federated learning enables big data for rare cancer boundary detection (vol 13, 7346, 2022)
Pati, Sarthak, Baid, Ujjwal, Edwards, Brandon, Sheller, Micah, Wang, Shih-Han, et al.
2023 - 3.11 Federated Learning and Reproducibility in Healthcare
Pati, Sarthak
Inverse Biophysical Modeling and Machine Learning in Personalized Oncology2023 - The Image Biomarker Standardization Initiative: Standardized convolutional filters for quantitative radiomics Authors and affiliations
Whybra, Philip, Zwanenburg, Alex, Andrearczyk, Vincent, Schaer, Roger, Apte, Aditya P, et al.
2023 - Panoptica--instance-wise evaluation of 3D semantic and instance segmentation maps
Kofler, Florian, M{\"o
arXiv preprint arXiv:2312.026082023 - The Brain Tumor Segmentation (BraTS) Challenge: Local Synthesis of Healthy Brain Tissue via Inpainting
Kofler, Florian, Meissen, Felix, Steinbauer, Felix, Graf, Robert, Ehrlich, Stefan K, et al.
arXiv preprint arXiv:2305.089922023
2022
- Federated Learning for the Classification of Tumor Infiltrating Lymphocytes
Baid, Ujjwal, Pati, Sarthak, Kurc, Tahsin, Gupta, Rajarsi, Bremer, Erich, et al.
arXiv preprint arXiv:2203.166222022 - Artificial-intelligence-driven volumetric breast density estimation with digital breast tomosynthesis in a racially diverse screening cohort.
Ahluwalia, Vinayak S, Mankowski, Walter, Pati, Sarthak, Bakas, Spyridon, Brooks, Ari D, et al.
2022 - MammoFL: Mammographic Breast Density Estimation using Federated Learning
Muthukrishnan, Ramya, Heyler, Angelina, Katti, Keshava, Pati, Sarthak, Mankowski, Walter, et al.
arXiv preprint arXiv:2206.055752022 - Deep-learning-enabled volumetric breast density estimation with digital breast tomosynthesis
Ahluwalia, Vinayak S, Mankowski, Walter, Pati, Sarthak, Bakas, Spyridon, Brooks, Ari, et al.
Cancer ResearchVol. 822022 - Expert tumor annotations and radiomics for locally advanced breast cancer in DCE-MRI for ACRIN 6657/I-SPY1
Chitalia, Rhea, Pati, Sarthak, Bhalerao, Megh, Thakur, Siddhesh Pravin, Jahani, Nariman, et al.
Scientific dataVol. 92022 - The University of Pennsylvania glioblastoma (UPenn-GBM) cohort: advanced MRI, clinical, genomics, \& radiomics
Bakas, Spyridon, Sako, Chiharu, Akbari, Hamed, Bilello, Michel, Sotiras, Aristeidis, et al.
Scientific dataVol. 92022 - The Federated Tumor Segmentation (FeTS) tool: an open-source solution to further solid tumor research
Pati, Sarthak, Baid, Ujjwal, Edwards, Brandon, Sheller, Micah J, Foley, Patrick, Reina, G Anthony, et al.
Physics in Medicine \& BiologyVol. 672022 - OpenFL: The Open Federated Learning library
Foley, Patrick, Sheller, Micah J, Edwards, Brandon, Pati, Sarthak, Riviera, Walter, et al.
Physics in Medicine \& BiologyVol. 672022 - Biomedical image analysis competitions: The state of current participation practice
Eisenmann, Matthias, Reinke, Annika, Weru, Vivienn, Tizabi, Minu Dietlinde, Isensee, Fabian, et al.
arXiv preprint arXiv:2212.085682022 - Federated learning enables big data for rare cancer boundary detection
Pati, Sarthak, Baid, Ujjwal, Edwards, Brandon, Sheller, Micah, Wang, Shih-Han, et al.
Nature CommunicationsVol. 132022 - NIMG-25. OPTIMIZATION OF ARTIFICIAL INTELLIGENCE ALGORITHMS FOR LOW-RESOURCE/CLINICAL ENVIRONMENTS: FOCUS ON CLINICALLY-RELEVANT GLIOMA REGION DELINEATION
Baheti, Bhakti, Thakur, Siddhesh, Pati, Sarthak, Karkada, Deepthi, Panchumarthy, Ravi, et al.
Neuro-OncologyVol. 242022 - Leveraging 2D deep learning ImageNet-trained models for native 3D medical image analysis
Baheti, Bhakti, Pati, Sarthak, Menze, Bjoern, Bakas, Spyridon
2022 - Summary of Best Papers Selected for the 2023 Edition of the IMIA Yearbook, Section Cancer Informatics (CI)
Pati, S, Baid, U, Edwards, B, Sheller, M, Wang, SH, et al.
IEEE/ACM Trans Comput Biol BioinformVol. 192022
2021
- Accurate and Robust Alignment of Differently Stained Histologic Images Based on Greedy Diffeomorphic Registration
Venet, Ludovic, Pati, Sarthak, Feldman, Michael D., Nasrallah, MacLean P., Yushkevich, Paul, Bakas, Spyridon
Applied SciencesVol. 112021 - The federated tumor segmentation (fets) challenge
Pati, Sarthak, Baid, Ujjwal, Zenk, Maximilian, Edwards, Brandon, Sheller, Micah, et al.
arXiv preprint arXiv:2105.058742021 - OpenFL: An open-source framework for Federated Learning
Reina, G Anthony, Gruzdev, Alexey, Foley, Patrick, Perepelkina, Olga, Sharma, Mansi, et al.
arXiv preprint arXiv:2105.064132021 - Federated Tumor Segmentation
Bakas, Spyridon, Sheller, Micah, Pati, Sarthak, Edwards, Brandon, Reina, G Anthony, et al.
zenodo.4573127Vol. 45731272021 - LabelFusion: Medical Image label fusion of segmentations
Pati, Sarthak, Baid, Ujjwal, Bakas, Spyridon
Zenodo2021 - The rsna-asnr-miccai brats 2021 benchmark on brain tumor segmentation and radiogenomic classification
Baid, Ujjwal, Ghodasara, Satyam, Mohan, Suyash, Bilello, Michel, Calabrese, Evan, et al.
arXiv preprint arXiv:2107.023142021 - Interactive machine learning-based multi-label segmentation of solid tumors and organs
Bounias, Dimitrios, Singh, Ashish, Bakas, Spyridon, Pati, Sarthak, Rathore, Saima, et al.
Applied SciencesVol. 112021 - Estimating glioblastoma biophysical growth parameters using deep learning regression
Pati, Sarthak, Sharma, Vaibhav, Aslam, Heena, Thakur, Siddhesh P, Akbari, Hamed, et al.
2021 - The Federated Tumor Segmentation (FeTS) Initiative: The First Real-World Large-Scale Data-Private Collaboration Focusing On Neuro-Oncology
Baid, Ujjwal, Pati, Sarthak, Thakur, Siddhesh, Edwards, Brandon, Sheller, Micah, et al.
Neuro-OncologyVol. 232021 - Classification of infection and ischemia in diabetic foot ulcers using vgg architectures
G{\"u
2021 - Optimization of deep learning based brain extraction in mri for low resource environments
Thakur, Siddhesh P, Pati, Sarthak, Panchumarthy, Ravi, Karkada, Deepthi, Wu, Junwen, et al.
2021 - Robust, primitive, and unsupervised quality estimation for segmentation ensembles
Kofler, Florian, Ezhov, Ivan, Fidon, Lucas, Pirkl, Carolin M, Paetzold, Johannes C, et al.
Frontiers in NeuroscienceVol. 152021
2020
- The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping
Zwanenburg, Alex, Valli{\`e
RadiologyVol. 2952020 - Cancer imaging phenomics via CaPTk: multi-institutional prediction of progression-free survival and pattern of recurrence in glioblastoma
Fathi Kazerooni, Anahita, Akbari, Hamed, Shukla, Gaurav, Badve, Chaitra, Rudie, Jeffrey D, et al.
JCO clinical cancer informaticsVol. 42020 - ANHIR: automatic non-rigid histological image registration challenge
Borovec, Ji{\v{r
IEEE transactions on medical imagingVol. 392020 - The cancer imaging phenomics toolkit (CaPTk): technical overview
Pati, Sarthak, Singh, Ashish, Rathore, Saima, Gastounioti, Aimilia, Bergman, Mark, et al.
2020 - Standardization in quantitative imaging: a multicenter comparison of radiomic features from different software packages on digital reference objects and patient data sets
McNitt-Gray, Michael, Napel, S, Jaggi, A, Mattonen, SA, Hadjiiski, L, et al.
TomographyVol. 62020 - Brain extraction on MRI scans in presence of diffuse glioma: Multi-institutional performance evaluation of deep learning methods and robust modality-agnostic training
Thakur, Siddhesh, Doshi, Jimit, Pati, Sarthak, Rathore, Saima, Sako, Chiharu, et al.
NeuroimageVol. 2202020 - Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data
Sheller, Micah J, Edwards, Brandon, Reina, G Anthony, Martin, Jason, Pati, Sarthak, et al.
Scientific reportsVol. 102020 - Standardised convolutional filtering for radiomics
Depeursinge, Adrien, Andrearczyk, Vincent, Whybra, Philip, van Griethuysen, Joost, M{\"u
arXiv preprint arXiv:2006.054702020 - Multi-institutional noninvasive in vivo characterization of IDH, 1p/19q, and EGFRvIII in glioma using neuro-Cancer Imaging Phenomics Toolkit (neuro-CaPTk)
Rathore, Saima, Mohan, Suyash, Bakas, Spyridon, Sako, Chiharu, Badve, Chaitra, et al.
Neuro-oncology advancesVol. 22020 - TMOD-09. GLIOBLASTOMA BIOPHYSICAL GROWTH ESTIMATION USING DEEP LEARNING-BASED REGRESSION
Pati, Sarthak, Sharma, Vaibhav, Aslam, Heena, Thakur, Siddhesh, Akbari, Hamed, et al.
Neuro-OncologyVol. 222020 - Reproducibility analysis of multi-institutional paired expert annotations and radiomic features of the Ivy Glioblastoma Atlas Project (Ivy GAP) dataset
Pati, Sarthak, Verma, Ruchika, Akbari, Hamed, Bilello, Michel, Hill, Virginia B, et al.
Medical physicsVol. 472020
2019
- Skull-stripping of glioblastoma MRI scans using 3D deep learning
Thakur, Siddhesh P, Doshi, Jimit, Pati, Sarthak, Ha, Sung Min, Sako, Chiharu, et al.
2019
2018
- Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome
Davatzikos, Christos, Rathore, Saima, Bakas, Spyridon, Pati, Sarthak, Bergman, Mark, et al.
Journal of medical imagingVol. 52018 - Brain cancer imaging phenomics toolkit (brain-CaPTk): an interactive platform for quantitative analysis of glioblastoma
Rathore, Saima, Bakas, Spyridon, Pati, Sarthak, Akbari, Hamed, Kalarot, Ratheesh, et al.
2018
2016
- GLISTRboost: combining multimodal MRI segmentation, registration, and biophysical tumor growth modeling with gradient boosting machines for glioma segmentation
Bakas, Spyridon, Zeng, Ke, Sotiras, Aristeidis, Rathore, Saima, Akbari, Hamed, et al.
2016 - Segmentation of gliomas in pre-operative and post-operative multimodal magnetic resonance imaging volumes based on a hybrid generative-discriminative framework
Zeng, Ke, Bakas, Spyridon, Sotiras, Aristeidis, Akbari, Hamed, Rozycki, Martin, et al.
2016
2013
- Accurate pose estimation using single marker single camera calibration system
Pati, Sarthak, Erat, Okan, Wang, Lejing, Weidert, Simon, Euler, Ekkehard, et al.
Vol. 86712013
2010
- Locomotion classification using EMG signal
Pati, Sarthak, Joshi, Deepak, Mishra, Ashutosh
2010
Reading one of these for a project?
Happy to talk through the methods, the data, or the parts that did not make it past peer review.
sarthak@verysafe.ai