[HTML][HTML] SynthStrip: skull-strip** for any brain image

A Hoopes, JS Mora, AV Dalca, B Fischl, M Hoffmann - NeuroImage, 2022‏ - Elsevier
The removal of non-brain signal from magnetic resonance imaging (MRI) data, known as
skull-strip**, is an integral component of many neuroimage analysis streams. Despite their …

NeSVoR: implicit neural representation for slice-to-volume reconstruction in MRI

J Xu, D Moyer, B Gagoski, JE Iglesias… - IEEE transactions on …, 2023‏ - ieeexplore.ieee.org
Reconstructing 3D MR volumes from multiple motion-corrupted stacks of 2D slices has
shown promise in imaging of moving subjects, eg, fetal MRI. However, existing slice-to …

Develo** and deploying deep learning models in brain magnetic resonance imaging: A review

K Aggarwal, M Manso Jimeno, KS Ravi… - NMR in …, 2023‏ - Wiley Online Library
Magnetic resonance imaging (MRI) of the brain has benefited from deep learning (DL) to
alleviate the burden on radiologists and MR technologists, and improve throughput. The …

Recent trends in AI applications for pelvic MRI: a comprehensive review

T Tsuboyama, M Yanagawa, T Fujioka, S Fujita… - La radiologia …, 2024‏ - Springer
Magnetic resonance imaging (MRI) is an essential tool for evaluating pelvic disorders
affecting the prostate, bladder, uterus, ovaries, and/or rectum. Since the diagnostic pathway …

Anatomy-aware and acquisition-agnostic joint registration with SynthMorph

M Hoffmann, A Hoopes, DN Greve, B Fischl… - Imaging …, 2024‏ - direct.mit.edu
Affine image registration is a cornerstone of medical-image analysis. While classical
algorithms can achieve excellent accuracy, they solve a time-consuming optimization for …

Fully automated planning for anatomical fetal brain MRI on 0.55 T

S Neves Silva, S McElroy… - Magnetic …, 2024‏ - Wiley Online Library
Purpose Widening the availability of fetal MRI with fully automatic real‐time planning of
radiological brain planes on 0.55 T MRI. Methods Deep learning‐based detection of key …

Synthetic data in generalizable, learning-based neuroimaging

K Gopinath, A Hoopes, DC Alexander… - Imaging …, 2024‏ - direct.mit.edu
Synthetic data have emerged as an attractive option for develo** machine-learning
methods in human neuroimaging, particularly in magnetic resonance imaging (MRI)—a …

Fetal neuroimaging updates

JN Stout, MA Bedoya, PE Grant… - … imaging clinics of North …, 2021‏ - pmc.ncbi.nlm.nih.gov
Fetal ultrasound (US) and magnetic resonance imaging (MRI) provide essential information
in the evaluation and management of pregnancies and have been shown to improve …

Synthetic data in generalizable, learning-based neuroimaging

S Laguna Cillero, K Gopinath… - Imaging …, 2024‏ - research-collection.ethz.ch
Synthetic data have emerged as an attractive option for develo** machine-learning
methods in human neuroimaging, particularly in magnetic resonance imaging (MRI)—a …

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

J Dadashkarimi, VP Trujillo, C Jaimes, L Zöllei… - arxiv preprint arxiv …, 2024‏ - arxiv.org
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 …