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WarpDrive: Improving spatial normalization using manual refinements

delete2024-01-01
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OA
AI
S
Simón Oxenford *
A
Ana Sofía Ríos
B
Barbara Hollunder
C
Clemens Neudorfer
A
Alexandre Boutet
G
Gavin J.B. Elias
J
Jürgen Germann
A
Aaron Loh
W
Wissam Deeb
B
Bryan Salvato
L
Leonardo Almeida
K
Kelly D. Foote
R
Robert Amaral
P
Paul B. Rosenberg
D
David F. Tang‐Wai
D
David A. Wolk
A
Anna Burke
M
Marwan N. Sabbagh
S
Stephen Salloway
M
M. Mallar Chakravarty
G
Gwenn S. Smith
C
Constantine G. Lyketsos
M
Michael S. Okun
W
William S. Anderson
Z
Zoltán Mari
F
Francisco A. Ponce
A
Andrés M. Lozano
W
Wolf‐Julian Neumann
B
Bassam Al‐Fatly
A
Andreas Horn
DOI:10.1016/j.media.2023.103041delete
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Abstract

Abstract

En 中文
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 3Dimaging data, also allowing refinements in high-resolution imaging, including histology , multiple modalities to precisely aggregate multiple data sources together.
Keywords:
Image normalization
Interactive registration
Deep brain stimulation

Journal

Medical Image Analysis cover
Medical Image Analysis
IF:
11.8
Papers:
3.9K
Citations:
2.4W

Organization

U
University of Florida
Scholars:
4.0W
Papers: 3.1W
Citations: 6.6W
B
Berlin Institute of Health
Scholars:
3.9W
Papers: 3.0W
Citations: 6.6K
U
UMass Chan Medical School
Scholars:
1.8K
Papers: 925
Citations: 28
H
Harvard University
Scholars:
26.5W
Papers: 22.0W
Citations: 28.7W
U
university of massachusetts system
Scholars:
3.9W
Papers: 3.6W
Citations: 42
F
Free University of Berlin
Scholars:
3.8W
Papers: 3.2W
Citations: 51
U
university health network toronto
Scholars:
1.7W
Papers: 1.4W
Citations: 19
H
Harvard Medical School
Scholars:
6.5W
Papers: 4.8W
Citations: 91
H
Humboldt University of Berlin
Scholars:
3.2W
Papers: 2.7W
Citations: 47
U
university of toronto
Scholars:
14.8W
Papers: 12.0W
Citations: 165
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Cited Papers

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errRios, Ana Sofia; Oxenford, Simon; Neudorfer, Clemens; Butenko, Konstantin; Li, Ningfei; Rajamani, Nanditha; Boutet, Alexandre; Elias, Gavin J. B.; Germann, Jurgen; Loh, Aaron; Deeb, Wissam; Wang, Fuyixue; Setsompop, Kawin; Salvato, Bryan; de Almeida, Leonardo Brito; Foote, Kelly D.; Amaral, Robert; Rosenberg, Paul B.; Tang-Wai, David F.; Wolk, David A.; Burke, Anna D.; Salloway, Stephen; Sabbagh, Marwan N.; Chakravarty, M. Mallar; Smith, Gwenn S.; Lyketsos, Constantine G.; Okun, Michael S.; Anderson, William S.; Mari, Zoltan; Ponce, Francisco A.; Lozano, Andres M.; Horn, Andreas
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