Adway U. Kanhere

Orcid: 0000-0001-5295-2634

According to our database1, Adway U. Kanhere authored at least 15 papers between 2022 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

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Bibliography

2025
Dual Energy CT for Deep Learning-Based Segmentation and Volumetric Estimation of Early Ischemic Infarcts.
J. Imaging Inform. Medicine, 2025

Optimizing Acute Stroke Segmentation on MRI Using Deep Learning: Self-Configuring Neural Networks Provide High Performance Using Only DWI Sequences.
J. Imaging Inform. Medicine, 2025

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, 2025

2024
ISLE: An Intelligent Streaming Framework for High-Throughput AI Inference in Medical Imaging.
J. Imaging Inform. Medicine, 2024

Improving Multi-Center Generalizability of GAN-Based Fat Suppression using Federated Learning.
CoRR, 2024

Anytime, Anywhere, Anyone: Investigating the Feasibility of Segment Anything Model for Crowd-Sourcing Medical Image Annotations.
CoRR, 2024

From Isolation to Collaboration: Federated Class-Heterogeneous Learning for Chest X-Ray Classification.
Proceedings of the Machine Learning for Health, 2024

Privacy-Preserving Collaboration for Multi-Organ Segmentation via Federated Learning from Sites with Partial Labels.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
One Copy Is All You Need: Resource-Efficient Streaming of Medical Imaging Data at Scale.
CoRR, 2023

High-Throughput AI Inference for Medical Image Classification and Segmentation using Intelligent Streaming.
CoRR, 2023

Text2Cohort: Democratizing the NCI Imaging Data Commons with Natural Language Cohort Discovery.
CoRR, 2023

Optimizing Federated Learning for Medical Image Classification on Distributed Non-iid Datasets with Partial Labels.
CoRR, 2023

SegViz: A Federated Learning Framework for Medical Image Segmentation from Distributed Datasets with Different and Incomplete Annotations.
CoRR, 2023

Surgical Aggregation: A Federated Learning Framework for Harmonizing Distributed Datasets with Diverse Tasks.
CoRR, 2023

2022
From Competition to Collaboration: Making Toy Datasets on Kaggle Clinically Useful for Chest X-Ray Diagnosis Using Federated Learning.
CoRR, 2022


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