22 citations · 26 across the 9 of their papers we have counts for
9 papers
: learning to disentangle technical distortions from true biological change
Jingru Fu, Kathleen E. Larson, Douglas N. Greve +2
Longitudinal MRI enables sensitive measurement of structural brain change for studying aging and neurodegenerative disease. Deformable image registration is a key tool for estimati…
Unified Brain Surface and Volume Registration
S. Mazdak Abulnaga, Andrew Hoopes, Malte Hoffmann +6
Accurate registration of brain MRI scans is fundamental for cross-subject analysis in neuroscientific studies. This involves aligning both the cortical surface of the brain and the…
Automated Segmentation of Coronal Brain Tissue Slabs for 3D Neuropathology
Jonathan Williams Ramirez, Dina Zemlyanker, Lucas Deden-Binder +15
Advances in image registration and machine learning have recently enabled volumetric analysis of postmortem brain tissue from conventional photographs of coronal slabs, which are r…
MultiMorph: On-demand Atlas Construction
S. Mazdak Abulnaga, Andrew Hoopes, Neel Dey +5
We present MultiMorph, a fast and efficient method for constructing anatomical atlases on the fly. Atlases capture the canonical structure of a collection of images and are essenti…
Learning accurate rigid registration for longitudinal brain MRI from synthetic data
Jingru Fu, Adrian V. Dalca, Bruce Fischl +2
Rigid registration aims to determine the translations and rotations necessary to align features in a pair of images. While recent machine learning methods have become state-of-the-…
Learn2Synth: Learning Optimal Data Synthesis Using Hypergradients for Brain Image Segmentation
Xiaoling Hu, Xiangrui Zeng, Oula Puonti +3
Domain randomization through synthesis is a powerful strategy to train networks that are unbiased with respect to the domain of the input images. Randomization allows networks to s…
Neurovascular Segmentation in sOCT with Deep Learning and Synthetic Training Data
Etienne Chollet, Yaël Balbastre, Chiara Mauri +3
Microvascular anatomy is known to be involved in various neurological disorders. However, understanding these disorders is hindered by the lack of imaging modalities capable of cap…
A label-free and data-free training strategy for vasculature segmentation in serial sectioning OCT data
Etienne Chollet, Yael Balbastre, Caroline Magnain +2
Serial sectioning Optical Coherence Tomography (sOCT) is a high-throughput, label free microscopic imaging technique that is becoming increasingly popular to study post-mortem neur…
Boosting Skull-Stripping Performance for Pediatric Brain Images
William Kelley, Nathan Ngo, Adrian V. Dalca +3
Skull-stripping is the removal of background and non-brain anatomical features from brain images. While many skull-stripping tools exist, few target pediatric populations. With the…