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20242026
most citedOOD-SEG: Exploiting out-of-distribution detection techniques for learning image segmentation from sparse multi-class positive-only annotations

2 citations · 2 across the 5 of their papers we have counts for

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eess.IV2025

crossMoDA Challenge: Evolution of Cross-Modality Domain Adaptation Techniques for Vestibular Schwannoma and Cochlea Segmentation from 2021 to 2023

Navodini Wijethilake, Reuben Dorent, Marina Ivory +39

The cross-Modality Domain Adaptation (crossMoDA) challenge series, initiated in 2021 in conjunction with the International Conference on Medical Image Computing and Computer Assist…

eess.IV2025

Systematic Review of Pituitary Gland and Pituitary Adenoma Automatic Segmentation Techniques in Magnetic Resonance Imaging

Mubaraq Yakubu, Navodini Wijethilake, Jonathan Shapey +2

Purpose: Accurate segmentation of both the pituitary gland and adenomas from magnetic resonance imaging (MRI) is essential for diagnosis and treatment of pituitary adenomas. This s…

eess.IV2025

A generalisable head MRI defacing pipeline: Evaluation on 2,566 meningioma scans

Lorena Garcia-Foncillas Macias, Aaron Kujawa, Aya Elshalakany +2

Reliable MRI defacing techniques to safeguard patient privacy while preserving brain anatomy are critical for research collaboration. Existing methods often struggle with incomplet…

eess.IV2024

Scribble-Based Interactive Segmentation of Medical Hyperspectral Images

Zhonghao Wang, Junwen Wang, Charlie Budd +3

Hyperspectral imaging (HSI) is an advanced medical imaging modality that captures optical data across a broad spectral range, providing novel insights into the biochemical composit…

eess.IV2024

A self-supervised and adversarial approach to hyperspectral demosaicking and RGB reconstruction in surgical imaging

Peichao Li, Oscar MacCormac, Jonathan Shapey +1

Hyperspectral imaging holds promises in surgical imaging by offering biological tissue differentiation capabilities with detailed information that is invisible to the naked eye. Fo…