MindGrab: A spectrally-motivated architecture for accessible deep learning in neuroimaging

Deployment complexity and specialized hardware requirements hinder the adoption of deep learning models in neuroimaging. We present MindGrab, a lightweight, fully convolutional model for volumetric skull stripping across the evaluated imaging modalities. MindGrab’s architecture is designed from firs...

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Bibliografische gegevens

Hoofdauteurs:	Armina Fani, Mike Doan, Isabelle Le, Alex Fedorov, Malte Hoffmann, Chris Rorden, Sergey Plis
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	Elsevier 2026-09-01
Reeks:	NeuroImage
Onderwerpen:	Skull stripping Neuroimaging Dilated convolutions Deep learning Zero footprint AI Omnimodal
Online toegang:	http://www.sciencedirect.com/science/article/pii/S1053811926003897
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