1 citations · 2 across the 13 of their papers we have counts for
15 papers
Deep Auxiliary Learning via Bilevel Feature Optimization for Label-Efficient Medical Image Segmentation
Fuping Wu, Xi Jia, Le Zhang +4
Auxiliary learning (AL), which can improve the performance of a primary task by leveraging related auxiliary tasks, is commonly regarded as a special case of multi-task learning. E…
Beyond the Encoder: Object-Centric Representations Emerging from Segmentation Foundation Models
Michalis Pistos, Bartłomiej W. Papież
Foundation models are increasingly used as feature extractors for downstream tasks with limited data, typically through representations obtained from their encoders. However, found…
When Two Tracers Disagree: An Investigation of Multimodal Fusion for Clinical PET/CT Segmentation
Jack A. Johnson, Bartłomiej W. Papież
PSMA and FDG PET/CT visualise complementary biological information in prostate cancer. Combining both tracers could capture heterogeneous tumour phenotypes that may be missed by ei…
Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces
Zuzanna A. Wakefield-Skórniewska, Bartłomiej W. Papież
Medical foundation models learn latent representations of clinically meaningful phenotypes, yet their ability to support controllable image generation remains largely unexplored. W…
PET/CT Radiogenomic Mutation Prediction in Non-Small Cell Lung Cancer Using Multi-Label Learning
Mona Furukawa, Sai Hyne, Daniel R. McGowan +1
Lung cancer remains one of the leading causes of cancer- related mortality worldwide. Although targeted therapies have improved outcomes for patients with non-small cell lung cance…
WBCBench 2026: A Challenge for Robust White Blood Cell Classification Under Class Imbalance
Xin Tian, Xudong Ma, Tianqi Yang +4
We present WBCBench 2026, an ISBI challenge and benchmark for automated WBC classification designed to stress-test algorithms under three key difficulties: (i) severe class imbalan…
Subgroups Matter for Robust Bias Mitigation
Anissa Alloula, Charles Jones, Ben Glocker +1
Despite the constant development of new bias mitigation methods for machine learning, no method consistently succeeds, and a fundamental question remains unanswered: when and why d…
Deep Neural Networks for Predicting Recurrence and Survival in Patients with Esophageal Cancer After Surgery
Yuhan Zheng, Jessie A Elliott, John V Reynolds +3
Esophageal cancer is a major cause of cancer-related mortality internationally, with high recurrence rates and poor survival even among patients treated with curative-intent surger…
On Biases in a UK Biobank-based Retinal Image Classification Model
Anissa Alloula, Rima Mustafa, Daniel R McGowan +1
Recent work has uncovered alarming disparities in the performance of machine learning models in healthcare. In this study, we explore whether such disparities are present in the UK…
Multimodal Deformable Image Registration for Long-COVID Analysis Based on Progressive Alignment and Multi-perspective Loss
Jiahua Li, James T. Grist, Fergus V. Gleeson +1
Long COVID is characterized by persistent symptoms, particularly pulmonary impairment, which necessitates advanced imaging for accurate diagnosis. Hyperpolarised Xenon-129 MRI (XeM…
TiBiX: Leveraging Temporal Information for Bidirectional X-ray and Report Generation
Santosh Sanjeev, Fadillah Adamsyah Maani, Arsen Abzhanov +4
With the emergence of vision language models in the medical imaging domain, numerous studies have focused on two dominant research activities: (1) report generation from Chest X-ra…
Autopet Challenge 2023: nnUNet-based whole-body 3D PET-CT Tumour Segmentation
Anissa Alloula, Daniel R McGowan, Bartłomiej W. Papież
Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) combined with Computed Tomography (CT) scans are critical in oncology to the identification of solid tumours and the monit…
Towards Automatic Scoring of Spinal X-ray for Ankylosing Spondylitis
Yuanhan Mo, Yao Chen, Aimee Readie +3
Manually grading structural changes with the modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS) on spinal X-ray imaging is costly and time-consuming due to bone shape comp…
An Ensemble Method to Automatically Grade Diabetic Retinopathy with Optical Coherence Tomography Angiography Images
Yuhan Zheng, Fuping Wu, Bartłomiej W. Papież
Diabetic retinopathy (DR) is a complication of diabetes, and one of the major causes of vision impairment in the global population. As the early-stage manifestation of DR is usuall…
Multimodal PET/CT Tumour Segmentation and Prediction of Progression-Free Survival using a Full-Scale UNet with Attention
Emmanuelle Bourigault, Daniel R. McGowan, Abolfazl Mehranian +1
Segmentation of head and neck (H\&N) tumours and prediction of patient outcome are crucial for patient's disease diagnosis and treatment monitoring. Current developments of robust…