Year: 2025
Type: article
Abstract: , reflecting the difficulties of achieving sub-mm precision with ~3 × 3 × 3 mm voxels. Our results also show that recon-any performs robustly across other sequences and contrasts, though thickness estimates are particularly sensitive and degrade substantially with anisotropic or low-resolution scans. We also validate our method on challenging postmortem LF-MRI scans, further illustrating its robustness. Our method represents a significant step toward making cortical surface analysis feasible for portable LF-MRI systems. The tool is publicly available at https://surfer.nmr.mgh.harvard.edu/fswiki/ReconAny.
Source: PubMed
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
Awards: Acquisition-independent machine learning for morphometric analysis of underrepresented aging populations with clinical and low-field brain MRI, Mapping the Human Connectome: Structure, Function, and Heritability, Novel technique for breast cancer screening and evaluation using ultra low field MRI, Alzheimer's Disease Neuroimaging Initiative, Open-source software for multi-scale mapping of the human brain, Measuring Brain Health Using Low-Field Portable MRI, Functionally guided adult whole brain cell atlas in human and NHP, Portable, Low Field Brain Magnetic Resonance Imaging (MRI) for Acute Stroke, Diagnosing the undiagnosable: studies of Alzheimer disease mimics and confounders via "neuropathometry" of dissection photos with 3D scanning
OpenAlex ID: W4417300585