Learning whole heart mesh generation from patient images for computational simulations
F Kong, SC Shadden - IEEE Transactions on Medical Imaging, 2022 - ieeexplore.ieee.org
Patient-specific cardiac modeling combines geometries of the heart derived from medical
images and biophysical simulations to predict various aspects of cardiac function. However …
images and biophysical simulations to predict various aspects of cardiac function. However …
Computation of a probabilistic and anisotropic failure metric on the aortic wall using a machine learning-based surrogate model
Scalar-valued failure metrics are commonly used to assess the risk of aortic aneurysm
rupture and dissection, which occurs under hypertensive blood pressures brought on by …
rupture and dissection, which occurs under hypertensive blood pressures brought on by …
Coupled reconstruction of cortical surfaces by diffeomorphic mesh deformation
Accurate reconstruction of cortical surfaces from brain magnetic resonance images (MRIs)
remains a challenging task due to the notorious partial volume effect in brain MRIs and the …
remains a challenging task due to the notorious partial volume effect in brain MRIs and the …
Patient-specific heart geometry modeling for solid biomechanics using deep learning
Automated volumetric meshing of patient-specific heart geometry can help expedite various
biomechanics studies, such as post-intervention stress estimation. Prior meshing techniques …
biomechanics studies, such as post-intervention stress estimation. Prior meshing techniques …
[HTML][HTML] Open-Full-Jaw: An open-access dataset and pipeline for finite element models of human jaw
Abstract Background: State-of-the-art finite element studies on human jaws are mostly
limited to the geometry of a single patient. In general, developing accurate patient-specific …
limited to the geometry of a single patient. In general, developing accurate patient-specific …
Whole-Heart Reconstruction with Explicit Topology Integrated Learning
Reconstruction and visualization of cardiac structures play significant roles in computer-
aided clinical practice as well as scientific research. With the advancement of medical …
aided clinical practice as well as scientific research. With the advancement of medical …
Reinforcement learning for block decomposition of planar CAD models
BC DiPrete, R Garimella, CG Cardona… - Engineering with …, 2024 - Springer
The problem of hexahedral mesh generation of general CAD models has vexed researchers
for over 3 decades and analysts often spend more than 50% of the design-analysis cycle …
for over 3 decades and analysts often spend more than 50% of the design-analysis cycle …
Reinforcement Learning for Block Decomposition of CAD Models
BC DiPrete, RV Garimella, CG Cardona… - arXiv preprint arXiv …, 2023 - arxiv.org
We present a novel AI-assisted method for decomposing (segmenting) planar CAD
(computer-aided design) models into well shaped rectangular blocks as a proof-of-principle …
(computer-aided design) models into well shaped rectangular blocks as a proof-of-principle …
Deep Medial Voxels: Learned Medial Axis Approximations for Anatomical Shape Modeling
Shape reconstruction from imaging volumes is a recurring need in medical image analysis.
Common workflows start with a segmentation step, followed by careful post-processing and …
Common workflows start with a segmentation step, followed by careful post-processing and …
Robust automated calcification meshing for biomechanical cardiac digital twins
Calcification has significant influence over cardiovascular diseases and interventions.
Detailed characterization of calcification is thus desired for predictive modeling, but calcified …
Detailed characterization of calcification is thus desired for predictive modeling, but calcified …