1 citations · 2 across the 5 of their papers we have counts for
5 papers
An MRI Atlas of the Human Fetal Brain: Reference and Segmentation Tools for Fetal Brain MRI Analysis
Mahdi Bagheri, Clemente Velasco-Annis, Jian Wang +10
Characterizing in-utero brain development is essential for understanding typical and atypical neurodevelopment. Building on prior spatiotemporal fetal brain MRI atlases, we present…
A Unified Deep Learning Framework for Motion Correction in Medical Imaging
Jian Wang, Razieh Faghihpirayesh, Danny Joca +2
Deep learning has shown significant value in medical image registration for motion correction, however, current techniques are either limited by the type and range of motion they c…
SpaER: Learning Spatio-temporal Equivariant Representations for Fetal Brain Motion Tracking
Jian Wang, Razieh Faghihpirayesh, Polina Golland +1
In this paper, we introduce SpaER, a pioneering method for fetal motion tracking that leverages equivariant filters and self-attention mechanisms to effectively learn spatio-tempor…
Fetal-BET: Brain Extraction Tool for Fetal MRI
Razieh Faghihpirayesh, Davood Karimi, Deniz Erdoğmuş +1
Fetal brain extraction is a necessary first step in most computational fetal brain MRI pipelines. However, it has been a very challenging task due to non-standard fetal head pose,…
Deep Learning Framework for Real-time Fetal Brain Segmentation in MRI
Razieh Faghihpirayesh, Davood Karimi, Deniz Erdogmus +1
Fetal brain segmentation is an important first step for slice-level motion correction and slice-to-volume reconstruction in fetal MRI. Fast and accurate segmentation of the fetal b…