activity
20242026
collaborators

8 papers

cs.CV2026

FPG-Seg: Annotation-free Retinal Vessel Topology Segmentation

James Willoughby, Irina Voiculescu

State-of-the art approaches to retinal vessel segmentation typically require extensive annotations, a highly time-consuming process, reliant on clinical expertise. We present FPG-S…

cs.CV2026

PLESS: Pseudo-Label Enhancement with Spreading Scribbles for Weakly Supervised Segmentation

Yeva Gabrielyan, Varduhi Yeghiazaryan, Irina Voiculescu

Weakly supervised learning with scribble annotations uses sparse user-drawn strokes to indicate segmentation labels on a small subset of pixels. This annotation reduces the cost of…

cs.CV2026

Reg4Pru: Regularisation Through Random Token Routing for Token Pruning

Julian Wyatt, Ronald Clark, Irina Voiculescu

Transformers are widely adopted in modern vision models due to their strong ability to scale with dataset size and generalisability. However, this comes with a major drawback: comp…

cs.LG2025

MUPAX: Multidimensional Problem Agnostic eXplainable AI

Vincenzo Dentamaro, Felice Franchini, Giuseppe Pirlo +1

Robust XAI techniques should ideally be simultaneously deterministic, model agnostic, and guaranteed to converge. We propose MULTIDIMENSIONAL PROBLEM AGNOSTIC EXPLAINABLE AI (MUPAX…

cs.CV2024

Entropy Bootstrapping for Weakly Supervised Nuclei Detection

James Willoughby, Irina Voiculescu

Microscopy structure segmentation, such as detecting cells or nuclei, generally requires a human to draw a ground truth contour around each instance. Weakly supervised approaches (…

cs.CV2024

Optimising for the Unknown: Domain Alignment for Cephalometric Landmark Detection

Julian Wyatt, Irina Voiculescu

Cephalometric Landmark Detection is the process of identifying key areas for cephalometry. Each landmark is a single GT point labelled by a clinician. A machine learning model pred…

cs.CV2024

Salt & Pepper Heatmaps: Diffusion-informed Landmark Detection Strategy

Julian Wyatt, Irina Voiculescu

Anatomical Landmark Detection is the process of identifying key areas of an image for clinical measurements. Each landmark is a single ground truth point labelled by a clinician. A…

cs.CV2024

Runtime Freezing: Dynamic Class Loss for Multi-Organ 3D Segmentation

James Willoughby, Irina Voiculescu

Segmentation has become a crucial pre-processing step to many refined downstream tasks, and particularly so in the medical domain. Even with recent improvements in segmentation mod…