Sarthak Pati

Orcid: 0000-0003-2243-8487

According to our database1, Sarthak Pati authored at least 58 papers between 2013 and 2025.

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Bibliography

2025
The MICCAI Federated Tumor Segmentation (FeTS) Challenge 2024: Efficient and Robust Aggregation Methods for Federated Learning.
CoRR, December, 2025



BrainLesion Suite: A Flexible and User-Friendly Framework for Modular Brain Lesion Image Analysis.
CoRR, July, 2025

BraTS orchestrator : Democratizing and Disseminating state-of-the-art brain tumor image analysis.
CoRR, June, 2025

Inclusive, Differentially Private Federated Learning for Clinical Data.
CoRR, May, 2025


From screening to subtyping in a single glance.
Patterns, 2025

Adapting to evolving MRI data: A transfer learning approach for Alzheimer's disease prediction.
NeuroImage, 2025

An Unsupervised Brain Extraction Quality Control Approach for Efficient Neuro-Oncology Studies.
J. Imaging Inform. Medicine, 2025

Optimization of deep learning models for inference in low resource environments.
Comput. Biol. Medicine, 2025

My Model Is Better Than Yours! Statistically-Aware Ranking for Fair Benchmarking of AI Models.
Proceedings of the Segmentation, Classification, and Synthesis for Brain Tumors and Traumatic Brain Injuries, 2025

2024






Privacy preservation for federated learning in health care.
Patterns, 2024

GaNDLF-Synth: A Framework to Democratize Generative AI for (Bio)Medical Imaging.
CoRR, 2024

BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023.
CoRR, 2024

Brain Tumor Segmentation (BraTS) Challenge 2024: Meningioma Radiotherapy Planning Automated Segmentation.
CoRR, 2024

BraTS-Path Challenge: Assessing Heterogeneous Histopathologic Brain Tumor Sub-regions.
CoRR, 2024

Best practices to evaluate the impact of biomedical research software - metric collection beyond citations.
Bioinform., 2024


Pan-Cancer Tumor Infiltrating Lymphocyte Detection based on Federated Learning.
Proceedings of the IEEE International Conference on Big Data, 2024

2023



Federated benchmarking of medical artificial intelligence with MedPerf.
Nat. Mac. Intell., July, 2023



Panoptica - instance-wise evaluation of 3D semantic and instance segmentation maps.
CoRR, 2023

Evaluation of software impact designed for biomedical research: Are we measuring what's meaningful?
CoRR, 2023

DENTEX: An Abnormal Tooth Detection with Dental Enumeration and Diagnosis Benchmark for Panoramic X-rays.
CoRR, 2023

GenerateCT: Text-Guided 3D Chest CT Generation.
CoRR, 2023

Why is the winner the best?
CoRR, 2023

Why is the Winner the Best?
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Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
MammoDL: Mammographic Breast Density Estimation using Federated Learning.
CoRR, 2022

Federated Learning Enables Big Data for Rare Cancer Boundary Detection.
CoRR, 2022

Federated Learning for the Classification of Tumor Infiltrating Lymphocytes.
CoRR, 2022

Leveraging 2D Deep Learning ImageNet-trained Models for Native 3D Medical Image Analysis.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2022

2021
The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification.
CoRR, 2021

OpenFL: An open-source framework for Federated Learning.
CoRR, 2021

The Federated Tumor Segmentation (FeTS) Challenge.
CoRR, 2021

GaNDLF: A Generally Nuanced Deep Learning Framework for Scalable End-to-End Clinical Workflows in Medical Imaging.
CoRR, 2021

Classification of Infection and Ischemia in Diabetic Foot Ulcers Using VGG Architectures.
Proceedings of the Diabetic Foot Ulcers Grand Challenge - Second Challenge, 2021

Optimization of Deep Learning Based Brain Extraction in MRI for Low Resource Environments.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2021

2020
ANHIR: Automatic Non-Rigid Histological Image Registration Challenge.
IEEE Trans. Medical Imaging, 2020

Brain extraction on MRI scans in presence of diffuse glioma: Multi-institutional performance evaluation of deep learning methods and robust modality-agnostic training.
NeuroImage, 2020

Estimating Glioblastoma Biophysical Growth Parameters Using Deep Learning Regression.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020

2019
Accurate and Robust Alignment of Variable-stained Histologic Images Using a General-purpose Greedy Diffeomorphic Registration Tool.
CoRR, 2019

Skull-Stripping of Glioblastoma MRI Scans Using 3D Deep Learning.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019


2017
Brain Cancer Imaging Phenomics Toolkit (brain-CaPTk): An Interactive Platform for Quantitative Analysis of Glioblastoma.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2017

2016
Segmentation of Gliomas in Pre-operative and Post-operative Multimodal Magnetic Resonance Imaging Volumes Based on a Hybrid Generative-Discriminative Framework.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2016

2015
GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2015

2013
Accurate pose estimation using single marker single camera calibration system.
Proceedings of the Medical Imaging 2013: Image-Guided Procedures, 2013


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