Article

Deep-diffeomorphic networks for conditional brain templates

2024-07-10

Abstract excerpt

Deformable brain templates are an important tool in many neuroimaging analyses. Conditional templates (e.g., age-specific templates) have advantages over single population templates by enabling improved registration accuracy and capturing common processes in brain development and degeneration. Conventional methods require large, evenly-spread cohorts to develop conditional templates, limiting their ability to crea...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 8a7dffdd-2c61-526b-8727-8184734ef6fc
DOI: 10.1101/2024.07.05.602288

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Deep-diffeomorphic networks for conditional brain templatesDOI 10.1101/2024.07.05.602288Read

Comparison of different methods for average anatomical templates creation: do we really gain anything from a diffeomorphic framework?Semantic proximity Read

Analyzing Brain Morphology in Alzheimer’s Disease Using Discriminative and Generative Spiral NetworksSemantic proximity Read

Learning Patterns of the Ageing Brain in MRI using Deep Convolutional NetworksSemantic proximity Read

Generalising the HCP multimodal cortical parcellation to UK BiobankSemantic proximity Read

MNI-FTD Templates: Unbiased Average Templates of Frontotemporal Dementia VariantsSemantic proximity Read

Generating Templates and Growth Charts for School-Aged Brain DevelopmentSemantic proximity Read

Learning patterns of the ageing brain in MRI using deep convolutional networks.Semantic proximity Read

TS-AI: A deep learning pipeline for multimodal subject-specific parcellation with task contrasts synthesisSemantic proximity Read

A Comparative Evaluation of Structural MRI Foundation Models for Age, Sex, and Body-Mass Index PredictionsSemantic proximity Read

Brain Age Prediction: Deep Models Need a Hand to GeneralizeSemantic proximity Read

From a deep learning model back to the brain - inferring morphological markers and their relation to agingSemantic proximity Read

Deep-Learning Cortical Registration Guided by Structural and Diffusion MRI and ConnectivitySemantic proximity Read