activity
20192026
most citedCrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea Segmentation

99 citations · 369 across the 31 of their papers we have counts for

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13 papers · 1 filter

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

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 +38

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

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…

eess.IV2023★ 1 cited

A Clinical Guideline Driven Automated Linear Feature Extraction for Vestibular Schwannoma

Navodini Wijethilake, Steve Connor, Anna Oviedova +3

Vestibular Schwannoma is a benign brain tumour that grows from one of the balance nerves. Patients may be treated by surgery, radiosurgery or with a conservative "wait-and-scan" st…

eess.IV2023★ 14 cited

Synthetic white balancing for intra-operative hyperspectral imaging

Anisha Bahl, Conor C. Horgan, Mirek Janatka +10

Hyperspectral imaging shows promise for surgical applications to non-invasively provide spatially-resolved, spectral information. For calibration purposes, a white reference image…

eess.IV2023★ 14 cited

Spatial gradient consistency for unsupervised learning of hyperspectral demosaicking: Application to surgical imaging

Peichao Li, Muhammad Asad, Conor Horgan +3

Hyperspectral imaging has the potential to improve intraoperative decision making if tissue characterisation is performed in real-time and with high-resolution. Hyperspectral snaps…

eess.IV2022★ 12 cited

Boundary Distance Loss for Intra-/Extra-meatal Segmentation of Vestibular Schwannoma

Navodini Wijethilake, Aaron Kujawa, Reuben Dorent +4

Vestibular Schwannoma (VS) typically grows from the inner ear to the brain. It can be separated into two regions, intrameatal and extrameatal respectively corresponding to being in…

eess.IV2022★ 99 cited

CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea Segmentation

Reuben Dorent, Aaron Kujawa, Marina Ivory +37

Domain Adaptation (DA) has recently raised strong interests in the medical imaging community. While a large variety of DA techniques has been proposed for image segmentation, most…

eess.IV2021

Deep Learning Approach for Hyperspectral Image Demosaicking, Spectral Correction and High-resolution RGB Reconstruction

Peichao Li, Michael Ebner, Philip Noonan +5

Hyperspectral imaging is one of the most promising techniques for intraoperative tissue characterisation. Snapshot mosaic cameras, which can capture hyperspectral data in a single…

eess.IV2020★ 65 cited

Manual segmentation versus semi-automated segmentation for quantifying vestibular schwannoma volume on MRI

Hari McGrath, Peichao Li, Reuben Dorent +6

Management of vestibular schwannoma (VS) is based on tumour size as observed on T1 MRI scans with contrast agent injection. Current clinical practice is to measure the diameter of…

eess.IV2019★ 50 cited

Automatic Segmentation of Vestibular Schwannoma from T2-Weighted MRI by Deep Spatial Attention with Hardness-Weighted Loss

Guotai Wang, Jonathan Shapey, Wenqi Li +7

Automatic segmentation of vestibular schwannoma (VS) tumors from magnetic resonance imaging (MRI) would facilitate efficient and accurate volume measurement to guide patient manage…