5 papers
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…
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network
Reza Akbari Movahed, Abuzar Rezaee, Arezoo Zakeri +3
Accurate cardiac motion estimation from cine cardiac magnetic resonance (CMR) images is vital for assessing cardiac function and detecting its abnormalities. Existing methods often…
An Efficient Model-Driven Groupwise Approach for Atlas Construction
Ziwei Zou, Bei Zou, Xiaoyan Kui +6
Atlas construction is fundamental to medical image analysis, offering a standardized spatial reference for tasks such as population-level anatomical modeling. While data-driven reg…
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…