Vishwa S. Parekh

39 papers B 1Misc 1Journal 31Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Children Are Not Small Adults: Addressing Limited Generalizability of an Adult Deep Learning CT Organ Segmentation Model to the Pediatric Population. J. Imaging Inform. Medicine Devina Chatterjee, Adway U. Kanhere, Florence X. Doo, Jerry Zhao, Andrew Chan, Alexander Welsh, Pranav Kulkarni, Annie Trang, Vishwa S. Parekh, Paul H. Yi
2025	J	`jnl`	Dual Energy CT for Deep Learning-Based Segmentation and Volumetric Estimation of Early Ischemic Infarcts. J. Imaging Inform. Medicine Peter I. Kamel, Mazhar Khalid, Rachel Steger, Adway U. Kanhere, Pranav Kulkarni, Vishwa S. Parekh, Paul H. Yi, Dheeraj Gandhi, Uttam Bodanapally
2025	—	`conf`	Generative Counterfactual Augmentation for Bias Mitigation. ICCVW Jason Uwaeze, Pranav Kulkarni, Vladimir Braverman, Michael A. Jacobs, Vishwa S. Parekh
2025	J	`jnl`	Optimizing Acute Stroke Segmentation on MRI Using Deep Learning: Self-Configuring Neural Networks Provide High Performance Using Only DWI Sequences. J. Imaging Inform. Medicine Peter I. Kamel, Adway U. Kanhere, Pranav Kulkarni, Mazhar Khalid, Rachel Steger, Uttam Bodanapally, Dheeraj Gandhi, Vishwa S. Parekh, Paul H. Yi
2025	J	`jnl`	Towards Fair Medical AI: Adversarial Debiasing of 3D CT Foundation Embeddings. CoRR Guangyao Zheng, Michael A. Jacobs, Vladimir Braverman, Vishwa S. Parekh
2024	J	`jnl`	A collective AI via lifelong learning and sharing at the edge. Nat. Mac. Intell. Andrea Soltoggio, Eseoghene Ben-Iwhiwhu, Vladimir Braverman, Eric Eaton, Benjamin Epstein, Yunhao Ge, Lucy Halperin, Jonathan P. How, Laurent Itti, Michael A. Jacobs, Pavan Kantharaju, Long Le, Steven Lee, Xinran Liu, Sildomar T. Monteiro, David Musliner, Saptarshi Nath, Priyadarshini Panda, Christos Peridis, Hamed Pirsiavash, Vishwa S. Parekh, Kaushik Roy, Shahaf S. Shperberg, Hava T. Siegelmann, Peter Stone, Kyle Vedder, Jingfeng Wu, Lin Yang, Guangyao Zheng, Soheil Kolouri
2024	J	`jnl`	Anytime, Anywhere, Anyone: Investigating the Feasibility of Segment Anything Model for Crowd-Sourcing Medical Image Annotations. CoRR Pranav Kulkarni, Adway U. Kanhere, Dharmam Savani, Andrew Chan, Devina Chatterjee, Paul H. Yi, Vishwa S. Parekh
2024	J	`jnl`	Demographic Predictability in 3D CT Foundation Embeddings. CoRR Guangyao Zheng, Michael A. Jacobs, Vishwa S. Parekh
2024	Misc	`conf`	Expanding the Horizon: Enabling Hybrid Quantum Transfer Learning for Long-Tailed Chest X-Ray Classification. QCE Skylar Chan, Pranav Kulkarni, Paul H. Yi, Vishwa S. Parekh
2024	J	`jnl`	Expanding the Horizon: Enabling Hybrid Quantum Transfer Learning for Long-Tailed Chest X-Ray Classification. CoRR Skylar Chan, Pranav Kulkarni, Paul H. Yi, Vishwa S. Parekh
2024	—	`conf`	From Isolation to Collaboration: Federated Class-Heterogeneous Learning for Chest X-Ray Classification. ML4H@NeurIPS Pranav Kulkarni, Adway U. Kanhere, Paul H. Yi, Vishwa S. Parekh
2024	J	`jnl`	Hidden in Plain Sight: Undetectable Adversarial Bias Attacks on Vulnerable Patient Populations. CoRR Pranav Kulkarni, Andrew Chan, Nithya Navarathna, Skylar Chan, Paul H. Yi, Vishwa S. Parekh
2024	J	`jnl`	ISLE: An Intelligent Streaming Framework for High-Throughput AI Inference in Medical Imaging. J. Imaging Inform. Medicine Pranav Kulkarni, Adway U. Kanhere, Eliot L. Siegel, Paul H. Yi, Vishwa S. Parekh
2024	J	`jnl`	Improving Multi-Center Generalizability of GAN-Based Fat Suppression using Federated Learning. CoRR Pranav Kulkarni, Adway U. Kanhere, Harshita Kukreja, Vivian Zhang, Paul H. Yi, Vishwa S. Parekh
2024	—	`conf`	Privacy-Preserving Collaboration for Multi-Organ Segmentation via Federated Learning from Sites with Partial Labels. CVPR Workshops Adway U. Kanhere, Pranav Kulkarni, Paul H. Yi, Vishwa S. Parekh
2023	J	`jnl`	A framework for dynamically training and adapting deep reinforcement learning models to different, low-compute, and continuously changing radiology deployment environments. CoRR Guangyao Zheng, Shuhao Lai, Vladimir Braverman, Michael A. Jacobs, Vishwa S. Parekh
2023	J	`jnl`	Asynchronous Decentralized Federated Lifelong Learning for Landmark Localization in Medical Imaging. CoRR Guangyao Zheng, Michael A. Jacobs, Vladimir Braverman, Vishwa S. Parekh
2023	J	`jnl`	High-Throughput AI Inference for Medical Image Classification and Segmentation using Intelligent Streaming. CoRR Pranav Kulkarni, Sean Garin, Adway U. Kanhere, Eliot L. Siegel, Paul H. Yi, Vishwa S. Parekh
2023	J	`jnl`	Multi-environment lifelong deep reinforcement learning for medical imaging. CoRR Guangyao Zheng, Shuhao Lai, Vladimir Braverman, Michael A. Jacobs, Vishwa S. Parekh
2023	J	`jnl`	One Copy Is All You Need: Resource-Efficient Streaming of Medical Imaging Data at Scale. CoRR Pranav Kulkarni, Adway U. Kanhere, Eliot L. Siegel, Paul H. Yi, Vishwa S. Parekh
2023	J	`jnl`	Optimizing Federated Learning for Medical Image Classification on Distributed Non-iid Datasets with Partial Labels. CoRR Pranav Kulkarni, Adway U. Kanhere, Paul H. Yi, Vishwa S. Parekh
2023	J	`jnl`	SegViz: A Federated Learning Framework for Medical Image Segmentation from Distributed Datasets with Different and Incomplete Annotations. CoRR Adway U. Kanhere, Pranav Kulkarni, Paul H. Yi, Vishwa S. Parekh
2023	J	`jnl`	Selective experience replay compression using coresets for lifelong deep reinforcement learning in medical imaging. CoRR Guangyao Zheng, Samson Zhou, Vladimir Braverman, Michael A. Jacobs, Vishwa S. Parekh
2023	J	`jnl`	Surgical Aggregation: A Federated Learning Framework for Harmonizing Distributed Datasets with Diverse Tasks. CoRR Pranav Kulkarni, Adway U. Kanhere, Paul H. Yi, Vishwa S. Parekh
2023	J	`jnl`	Text2Cohort: Democratizing the NCI Imaging Data Commons with Natural Language Cohort Discovery. CoRR Pranav Kulkarni, Adway U. Kanhere, Paul H. Yi, Vishwa S. Parekh
2022	J	`jnl`	From Competition to Collaboration: Making Toy Datasets on Kaggle Clinically Useful for Chest X-Ray Diagnosis Using Federated Learning. CoRR Pranav Kulkarni, Adway U. Kanhere, Paul H. Yi, Vishwa S. Parekh
2021	J	`jnl`	Cross-Domain Federated Learning in Medical Imaging. CoRR Vishwa S. Parekh, Shuhao Lai, Vladimir Braverman, Jeff Leal, Steven Rowe, Jay J. Pillai, Michael A. Jacobs
2020	—	`conf`	Multitask radiological modality invariant landmark localization using deep reinforcement learning. MIDL Vishwa S. Parekh, Alex E. Bocchieri, Vladimir Braverman, Michael A. Jacobs
2019	J	`jnl`	Multiparametric Deep Learning Tissue Signatures for Muscular Dystrophy: Preliminary Results. CoRR Alex E. Bocchieri, Vishwa S. Parekh, Kathryn R. Wagner, Shivani Ahlawat, Vladimir Braverman, Doris G. Leung, Michael A. Jacobs
2019	J	`jnl`	Multiparametric Deep Learning and Radiomics for Tumor Grading and Treatment Response Assessment of Brain Cancer: Preliminary Results. CoRR Vishwa S. Parekh, John Laterra, Chetan Bettegowda, Alex E. Bocchieri, Jay J. Pillai, Michael A. Jacobs
2019	—	`conf`	Radiomic Synthesis Using Deep Convolutional Neural Networks. ISBI Vishwa S. Parekh, Michael A. Jacobs
2019	J	`jnl`	Tumor Connectomics: Mapping the intra-tumoral complex interaction network. CoRR Vishwa S. Parekh, Michael A. Jacobs
2018	J	`jnl`	Advanced machine learning informatics modeling using clinical and radiological imaging metrics for characterizing breast tumor characteristics with the OncotypeDX gene array. CoRR Michael A. Jacobs, Christopher Umbricht, Vishwa S. Parekh, Riham El Khouli, Leslie Cope, Katarzyna J. Macura, Susan C. Harvey, Antonio C. Wolff
2018	J	`jnl`	MPRAD: A Multiparametric Radiomics Framework. CoRR Vishwa S. Parekh, Michael A. Jacobs
2018	J	`jnl`	Multiparametric Deep Learning Tissue Signatures for a Radiological Biomarker of Breast Cancer: Preliminary Results. CoRR Vishwa S. Parekh, Katarzyna J. Macura, Susan C. Harvey, Ihab Kamel, Riham El Khouli, David A. Bluemke, Michael A. Jacobs
2018	J	`jnl`	Radiomic Synthesis Using Deep Convolutional Neural Networks. CoRR Vishwa S. Parekh, Michael A. Jacobs
2016	—	`conf`	A multidimensional data visualization and clustering method: Consensus similarity mapping. ISBI Vishwa S. Parekh, Michael A. Jacobs
2016	J	`jnl`	Unsupervised Non Linear Dimensionality Reduction Machine Learning methods applied to Multiparametric MRI in cerebral ischemia: Preliminary Results. CoRR Vishwa S. Parekh, Jeremy R. Jacobs, Michael A. Jacobs
2014	B	`conf`	Unsupervised nonlinear dimensionality reduction machine learning methods applied to multiparametric MRI in cerebral ischemia: preliminary results. Image Processing Vishwa S. Parekh, Jeremy R. Jacobs, Michael A. Jacobs