31 citations · 46 across the 4 of their papers we have counts for
4 papers
Improving the Segmentation of Pediatric Low-Grade Gliomas through Multitask Learning
Partoo Vafaeikia, Matthias W. Wagner, Uri Tabori +2
Brain tumor segmentation is a critical task for tumor volumetric analyses and AI algorithms. However, it is a time-consuming process and requires neuroradiology expertise. While th…
Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: Evaluation in Alzheimer's disease
Martin Dyrba, Moritz Hanzig, Slawek Altenstein +37
Background: Although convolutional neural networks (CNN) achieve high diagnostic accuracy for detecting Alzheimer's disease (AD) dementia based on magnetic resonance imaging (MRI)…
Bayesian Pharmacokinetic Modeling of Dynamic Contrast-Enhanced Magnetic Resonance Imaging: Validation and Application
Andreas Mittermeier, Birgit Ertl-Wagner, Jens Ricke +2
Tracer-kinetic analysis of dynamic contrast-enhanced magnetic resonance imaging data is commonly performed with the well-known Tofts model and nonlinear least squares (NLLS) regres…
Hough-CNN: Deep Learning for Segmentation of Deep Brain Regions in MRI and Ultrasound
Fausto Milletari, Seyed-Ahmad Ahmadi, Christine Kroll +8
In this work we propose a novel approach to perform segmentation by leveraging the abstraction capabilities of convolutional neural networks (CNNs). Our method is based on Hough vo…