SIRE: scale-invariant, rotation-equivariant estimation of artery orientations using graph neural networks
Blood vessel orientation as visualized in 3D medical images is an important descriptor of its
geometry that can be used for centerline extraction and subsequent segmentation and …
geometry that can be used for centerline extraction and subsequent segmentation and …
VesselVAE: Recursive Variational Autoencoders for 3D Blood Vessel Synthesis
We present a data-driven generative framework for synthesizing blood vessel 3D geometry.
This is a challenging task due to the complexity of vascular systems, which are highly …
This is a challenging task due to the complexity of vascular systems, which are highly …
Tiavox: Time-aware attenuation voxels for sparse-view 4d dsa reconstruction
Four-dimensional Digital Subtraction Angiography (4D DSA) plays a critical role in the
diagnosis of many medical diseases, such as Arteriovenous Malformations (AVM) and …
diagnosis of many medical diseases, such as Arteriovenous Malformations (AVM) and …
Shape of my heart: Cardiac models through learned signed distance functions
The efficient construction of anatomical models is one of the major challenges of patient-
specific in-silico models of the human heart. Current methods frequently rely on linear …
specific in-silico models of the human heart. Current methods frequently rely on linear …
TrIND: Representing Anatomical Trees by Denoising Diffusion of Implicit Neural Fields
A Sinha, G Hamarneh - … Conference on Medical Image Computing and …, 2024 - Springer
Anatomical trees play a central role in clinical diagnosis and treatment planning. However,
accurately representing anatomical trees is challenging due to their varying and complex …
accurately representing anatomical trees is challenging due to their varying and complex …
Implicit neural representations for modeling of abdominal aortic aneurysm progression
Abdominal aortic aneurysms (AAAs) are progressive dilatations of the abdominal aorta that,
if left untreated, can rupture with lethal consequences. Imaging-based patient monitoring is …
if left untreated, can rupture with lethal consequences. Imaging-based patient monitoring is …
[HTML][HTML] Implicit neural representations for unsupervised super-resolution and denoising of 4D flow MRI
Background and Objective: 4D flow magnetic resonance imaging provides time-resolved
blood flow velocity measurements, but suffers from limitations in spatio-temporal resolution …
blood flow velocity measurements, but suffers from limitations in spatio-temporal resolution …
ReSDF: Redistancing implicit surfaces using neural networks
This paper proposes a deep-learning-based method for recovering a signed distance
function (SDF) of a given hypersurface represented by an implicit level set function. Using …
function (SDF) of a given hypersurface represented by an implicit level set function. Using …
Representing Anatomical Trees by Denoising Diffusion of Implicit Neural Fields
A Sinha, G Hamarneh - arXiv preprint arXiv:2403.08974, 2024 - arxiv.org
Anatomical trees play a central role in clinical diagnosis and treatment planning. However,
accurately representing anatomical trees is challenging due to their varying and complex …
accurately representing anatomical trees is challenging due to their varying and complex …
Enhancing Dynamic CT Image Reconstruction with Neural Fields Through Explicit Motion Regularizers
Image reconstruction for dynamic inverse problems with highly undersampled data poses a
major challenge: not accounting for the dynamics of the process leads to a non-realistic …
major challenge: not accounting for the dynamics of the process leads to a non-realistic …