output
20212024
most citedBrain tumour segmentation using a triplanar ensemble of U-Nets

21 citations

5 papers

cs.LG2024★ 10 cited

LLpowershap: Logistic Loss-based Automated Shapley Values Feature Selection Method

Iqbal Madakkatel, Elina Hyppönen

Shapley values have been used extensively in machine learning, not only to explain black box machine learning models, but among other tasks, also to conduct model debugging, sensit…

physics.med-ph2022★ 4 cited

Close contact restriction periods for patients who received iodine-131 therapy for differentiated thyroid cancer

Jake C. Forster, Daniel Badger, Kevin J. Hickson

Objective. Patients treated with radionuclide therapy may require restrictions on certain activities for a period of time following treatment to optimise protection of the public a…

eess.IV2022★ 11 cited

Mutual information neural estimation for unsupervised multi-modal registration of brain images

Gerard Snaauw, Michele Sasdelli, Gabriel Maicas +4

Many applications in image-guided surgery and therapy require fast and reliable non-linear, multi-modal image registration. Recently proposed unsupervised deep learning-based regis…

eess.IV2021★ 21 cited

Brain tumour segmentation using a triplanar ensemble of U-Nets

Vaanathi Sundaresan, Ludovica Griffanti, Mark Jenkinson

Gliomas appear with wide variation in their characteristics both in terms of their appearance and location on brain MR images, which makes robust tumour segmentation highly challen…

cs.CV2021★ 6 cited

Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning

Yu Tian, Guansong Pang, Yuanhong Chen +3

Anomaly detection with weakly supervised video-level labels is typically formulated as a multiple instance learning (MIL) problem, in which we aim to identify snippets containing a…