1 citations · 1 across the 6 of their papers we have counts for
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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…
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…
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…
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…
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…
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…