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researcher

Tamas Gonda

4 papers hereh-index 211 citations21 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • eess.IV2

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedIPMN Risk Assessment under Federated Learning Paradigm

1 citations · 1 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2026

CrossPan: A Comprehensive Benchmark for Cross-Sequence Pancreas MRI Segmentation and Generalization

Linkai Peng, Cuiling Sun, Zheyuan Zhang +10

Automatic pancreas segmentation is fundamental to abdominal MRI analysis, yet deep learning models trained on one MRI sequence often fail catastrophically when applied to another-a…

cs.CV2025

Pancreas Part Segmentation under Federated Learning Paradigm

Ziliang Hong, Halil Ertugrul Aktas, Andrea Mia Bejar +15

We present the first federated learning (FL) approach for pancreas part(head, body and tail) segmentation in MRI, addressing a critical clinical challenge as a significant innovati…

eess.IV2024★ 1 cited

IPMN Risk Assessment under Federated Learning Paradigm

Hongyi Pan, Ziliang Hong, Gorkem Durak +17

Accurate classification of Intraductal Papillary Mucinous Neoplasms (IPMN) is essential for identifying high-risk cases that require timely intervention. In this study, we develop…

eess.IV2024

Adaptive Aggregation Weights for Federated Segmentation of Pancreas MRI

Hongyi Pan, Gorkem Durak, Zheyuan Zhang +16

Federated learning (FL) enables collaborative model training across institutions without sharing sensitive data, making it an attractive solution for medical imaging tasks. However…

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