WarpDrive: Improving spatial normalization using manual refinements

Simón Oxenford, Ana Sofía Ríos, Barbara Hollunder, Clemens Neudorfer, Alexandre Boutet, Gavin J.B. Elias, Jurgen Germann, Aaron Loh, Wissam Deeb, Bryan Salvato, Leonardo Almeida, Kelly D. Foote, Robert Amaral, Paul B. Rosenberg, David F. Tang-Wai, David A. Wolk, Anna D. Burke, Marwan N. Sabbagh, Stephen Salloway, M. Mallar ChakravartyGwenn S. Smith, Constantine G. Lyketsos, Michael S. Okun, William S. Anderson, Zoltan Mari, Francisco A. Ponce, Andres Lozano, Wolf Julian Neumann, Bassam Al-Fatly, Andreas Horn

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Spatial normalization—the process of mapping subject brain images to an average template brain—has evolved over the last 20+ years into a reliable method that facilitates the comparison of brain imaging results across patients, centers & modalities. While overall successful, sometimes, this automatic process yields suboptimal results, especially when dealing with brains with extensive neurodegeneration and atrophy patterns, or when high accuracy in specific regions is needed. Here we introduce WarpDrive, a novel tool for manual refinements of image alignment after automated registration. We show that the tool applied in a cohort of patients with Alzheimer's disease who underwent deep brain stimulation surgery helps create more accurate representations of the data as well as meaningful models to explain patient outcomes. The tool is built to handle any type of 3D imaging data, also allowing refinements in high-resolution imaging, including histology and multiple modalities to precisely aggregate multiple data sources together.

Original languageEnglish (US)
Article number103041
JournalMedical Image Analysis
Volume91
DOIs
StatePublished - Jan 2024

Bibliographical note

Publisher Copyright:
© 2023

Keywords

  • Deep brain stimulation
  • Image normalization
  • Interactive registration

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