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

87 citations · 299 across the 14 of their papers we have counts for

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6 papers · 1 filter

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…

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…

eess.IV2023

Explainable unsupervised multi-modal image registration using deep networks

Chengjia Wang, Giorgos Papanastasiou

Clinical decision making from magnetic resonance imaging (MRI) combines complementary information from multiple MRI sequences (defined as 'modalities'). MRI image registration aims…

eess.IV2022

Unsupervised Image Registration Towards Enhancing Performance and Explainability in Cardiac And Brain Image Analysis

Chengjia Wang, Guang Yang, Giorgos Papanastasiou

Magnetic Resonance Imaging (MRI) typically recruits multiple sequences (defined here as "modalities"). As each modality is designed to offer different anatomical and functional cli…

eess.IV2020★ 1 cited

Max-Fusion U-Net for Multi-Modal Pathology Segmentation with Attention and Dynamic Resampling

Haochuan Jiang, Chengjia Wang, Agisilaos Chartsias +1

Automatic segmentation of multi-sequence (multi-modal) cardiac MR (CMR) images plays a significant role in diagnosis and management for a variety of cardiac diseases. However, the…

eess.IV2019★ 69 cited

Learning to synthesise the ageing brain without longitudinal data

Tian Xia, Agisilaos Chartsias, Chengjia Wang +1

How will my face look when I get older? Or, for a more challenging question: How will my brain look when I get older? To answer this question one must devise (and learn from data)…