367 citations · 383 across the 3 of their papers we have counts for
6 papers
Rapid head-pose detection for automated slice prescription of fetal-brain MRI
Malte Hoffmann, Esra Abaci Turk, Borjan Gagoski +8
In fetal-brain MRI, head-pose changes between prescription and acquisition present a challenge to obtaining the standard sagittal, coronal and axial views essential to clinical ass…
Learning Anatomical Segmentations for Tractography from Diffusion MRI
Christian Ewert, David Kügler, Anastasia Yendiki +1
Deep learning approaches for diffusion MRI have so far focused primarily on voxel-based segmentation of lesions or white-matter fiber tracts. A drawback of representing tracts as v…
FastSurfer -- A fast and accurate deep learning based neuroimaging pipeline
Leonie Henschel, Sailesh Conjeti, Santiago Estrada +3
Traditional neuroimage analysis pipelines involve computationally intensive, time-consuming optimization steps, and thus, do not scale well to large cohort studies with thousands o…
FatSegNet : A Fully Automated Deep Learning Pipeline for Adipose Tissue Segmentation on Abdominal Dixon MRI
Santiago Estrada, Ran Lu, Sailesh Conjeti +4
Purpose: Development of a fast and fully automated deep learning pipeline (FatSegNet) to accurately identify, segment, and quantify abdominal adipose tissue on Dixon MRI from the R…
Complex Fully Convolutional Neural Networks for MR Image Reconstruction
Muneer Ahmad Dedmari, Sailesh Conjeti, Santiago Estrada +3
Undersampling the k-space data is widely adopted for acceleration of Magnetic Resonance Imaging (MRI). Current deep learning based approaches for supervised learning of MRI image r…
DeepNAT: Deep Convolutional Neural Network for Segmenting Neuroanatomy
Christian Wachinger, Martin Reuter, Tassilo Klein
We introduce DeepNAT, a 3D Deep convolutional neural network for the automatic segmentation of NeuroAnaTomy in T1-weighted magnetic resonance images. DeepNAT is an end-to-end learn…