386 citations · 444 across the 8 of their papers we have counts for
4 papers · 1 filter
DeepASL: Kinetic Model Incorporated Loss for Denoising Arterial Spin Labeled MRI via Deep Residual Learning
Cagdas Ulas, Giles Tetteh, Stephan Kaczmarz +2
Arterial spin labeling (ASL) allows to quantify the cerebral blood flow (CBF) by magnetic labeling of the arterial blood water. ASL is increasingly used in clinical studies due to…
Direct Estimation of Pharmacokinetic Parameters from DCE-MRI using Deep CNN with Forward Physical Model Loss
Cagdas Ulas, Giles Tetteh, Michael J. Thrippleton +5
Dynamic contrast-enhanced (DCE) MRI is an evolving imaging technique that provides a quantitative measure of pharmacokinetic (PK) parameters in body tissues, in which series of T1-…
Btrfly Net: Vertebrae Labelling with Energy-based Adversarial Learning of Local Spine Prior
Anjany Sekuboyina, Markus Rempfler, Jan Kukačka +4
Robust localisation and identification of vertebrae is essential for automated spine analysis. The contribution of this work to the task is two-fold: (1) Inspired by the human expe…
DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes
Giles Tetteh, Velizar Efremov, Nils D. Forkert +6
We present DeepVesselNet, an architecture tailored to the challenges faced when extracting vessel networks or trees and corresponding features in 3-D angiographic volumes using dee…