activity
20182026
most citedIs attention all you need in medical image analysis? A review

87 citations · 155 across the 17 of their papers we have counts for

collaborators

23 papers

cs.AI2026

From Training to Deployment: Post-Hoc Causal Feature Identification via Sensitivity Ratios

Athanasios Vlontzos, Giorgos Papanastasiou, Bernhard Kainz +1

Given a model that is already trained, which features does it rely on causally versus spuriously? Existing methods require access to the training procedure and cannot answer this p…

cs.AI2026

Entangled by Design: Spurious Intra-Variable Signal Routing in Tabular In-Context Learners

Athanasios Vlontzos, Giorgos Papanastasiou, Bernhard Kainz +1

Consider a model trained at a single hospital to predict patient recovery, where the measured feature bundles the patient's true health signal () with a systematic artefact…

cs.CV2025

Causally Steered Diffusion for Automated Video Counterfactual Generation

Nikos Spyrou, Athanasios Vlontzos, Paraskevas Pegios +5

Adapting text-to-image (T2I) latent diffusion models (LDMs) to video editing has shown strong visual fidelity and controllability, but challenges remain in maintaining causal relat…

eess.IV2025

A Novel Coronary Artery Registration Method Based on Super-pixel Particle Swarm Optimization

Peng Qi, Wenxi Qu, Tianliang Yao +5

Percutaneous Coronary Intervention (PCI) is a minimally invasive procedure that improves coronary blood flow and treats coronary artery disease. Although PCI typically requires 2D…

cs.AI2025

Reason Like a Radiologist: Chain-of-Thought and Reinforcement Learning for Verifiable Report Generation

Peiyuan Jing, Kinhei Lee, Zhenxuan Zhang +7

Radiology report generation is critical for efficiency but current models lack the structured reasoning of experts, hindering clinical trust and explainability by failing to link v…

eess.IV2025

Semi-Supervised Medical Image Segmentation via Knowledge Mining from Large Models

Yuchen Mao, Hongwei Li, Yinyi Lai +4

Large-scale vision models like SAM have extensive visual knowledge, yet their general nature and computational demands limit their use in specialized tasks like medical image segme…