activity
20192025
most citedInfant FreeSurfer: An automated segmentation and surface extraction pipeline for T1-weighted neuroimaging data of infants 0-2 years

223 citations · 299 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2025

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…

eess.IV2024

Search Wide, Focus Deep: Automated Fetal Brain Extraction with Sparse Training Data

Javid Dadashkarimi, Valeria Pena Trujillo, Camilo Jaimes +2

Automated fetal brain extraction from full-uterus MRI is a challenging task due to variable head sizes, orientations, complex anatomy, and prevalent artifacts. While deep-learning…

eess.IV2024★ 22 cited

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…

cs.CV2023

VINNA for Neonates -- Orientation Independence through Latent Augmentations

Leonie Henschel, David Kügler, Lilla Zöllei +1

Fast and accurate segmentation of neonatal brain images is highly desired to better understand and detect changes during development and disease. Yet, the limited availability of g…

eess.IV2020★ 49 cited

Cortical surface registration using unsupervised learning

Jieyu Cheng, Adrian V. Dalca, Bruce Fischl +1

Non-rigid cortical registration is an important and challenging task due to the geometric complexity of the human cortex and the high degree of inter-subject variability. A convent…

eess.IV2020★ 223 cited

Infant FreeSurfer: An automated segmentation and surface extraction pipeline for T1-weighted neuroimaging data of infants 0-2 years

Lilla Zöllei, Juan Eugenio Iglesias, Yangming Ou +2

The development of automated tools for brain morphometric analysis in infants has lagged significantly behind analogous tools for adults. This gap reflects the greater challenges i…

cs.CV2019★ 5 cited

Fast Infant MRI Skullstripping with Multiview 2D Convolutional Neural Networks

Amod Jog, P. Ellen Grant, Joseph L. Jacobson +4

Skullstripping is defined as the task of segmenting brain tissue from a full head magnetic resonance image~(MRI). It is a critical component in neuroimage processing pipelines. Dow…