papers

Publications (11)

cs.CV2026

DINO-3DRA: Leveraging 2D Foundation Model Semantics for 3D Cerebral Aneurysm Segmentation

Jiayang Lu, Fengming Lin, Alejandro F. Frangi +1

Accurate aneurysm segmentation in 3D rotational angiography (3DRA) is hindered by extreme class imbalance, morphological similarity to vessels, and absent large-scale 3D pretrainin…

cs.CV2026

Conditional Latent Diffusion Model with Fourier-based Motion Modelling for Virtual Population Synthesis

Shaokun Lan, Haoran Dou, Jinghan Huang +5

In-silico trials of medical devices require the generation of virtual populations of anatomies. In cardiovascular applications, virtual anatomy is typically represented as a 3D+t m…

cs.CV2025

Vision Language Models: A Survey of 26K Papers

Fengming Lin

We present a transparent, reproducible measurement of research trends across 26,104 accepted papers from CVPR, ICLR, and NeurIPS spanning 2023-2025. Titles and abstracts are normal…

cs.CV2024

Unsupervised Domain Adaptation for Brain Vessel Segmentation through Transwarp Contrastive Learning

Fengming Lin, Yan Xia, Michael MacRaild +6

Unsupervised domain adaptation (UDA) aims to align the labelled source distribution with the unlabelled target distribution to obtain domain-invariant predictive models. Since cros…

cs.CV2019

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Spyridon Bakas, Mauricio Reyes, Andras Jakab +421

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritum…

cs.CV2026

HeartVolMesh: Cardiac Volumetric Mesh Reconstruction via Covariance-Guided Graph Deformation

Fengming Lin, Arezoo Zakeri, Haoran Dou +4

Accurate patient-specific tetrahedral cardiac meshes are essential for in-silico trials, yet common segmentation-then-modelling pipelines can blur thin-wall anatomy and offer limit…

cs.CV2026

Reg-TTR, Test-Time Refinement for Fast, Robust and Accurate Image Registration

Lin Chen, Yue He, Fengting Zhang +4

Traditional image registration methods are robust but slow due to their iterative nature. While deep learning has accelerated inference, it often struggles with domain shifts. Emer…

eess.IV2023

Adaptive Semi-Supervised Segmentation of Brain Vessels with Ambiguous Labels

Fengming Lin, Yan Xia, Nishant Ravikumar +3

Accurate segmentation of brain vessels is crucial for cerebrovascular disease diagnosis and treatment. However, existing methods face challenges in capturing small vessels and hand…

eess.IV2026

SMILE-UHURA Challenge -- Small Vessel Segmentation at Mesoscopic Scale from Ultra-High Resolution 7T Magnetic Resonance Angiograms

Soumick Chatterjee, Hendrik Mattern, Marc Dörner +45

The human brain receives nutrients and oxygen through an intricate network of blood vessels. Pathology affecting small vessels, at the mesoscopic scale, represents a critical vulne…

cs.CV2024

GS-EMA: Integrating Gradient Surgery Exponential Moving Average with Boundary-Aware Contrastive Learning for Enhanced Domain Generalization in Aneurysm Segmentation

Fengming Lin, Yan Xia, Michael MacRaild +6

The automated segmentation of cerebral aneurysms is pivotal for accurate diagnosis and treatment planning. Confronted with significant domain shifts and class imbalance in 3D Rotat…

cs.CV2025

From Pixels to Polygons: A Survey of Deep Learning Approaches for Medical Image-to-Mesh Reconstruction

Fengming Lin, Arezoo Zakeri, Yidan Xue +7

Deep learning-based medical image-to-mesh reconstruction has rapidly evolved, enabling the transformation of medical imaging data into three-dimensional mesh models that are critic…