Deformable model reconstruction of the subarachnoid space

Jeffrey Glaister; Muhan Shao; Xiang Li; Aaron Carass; Snehashis Roy; Ari M. Blitz; Jerry L. Prince; Lotta M. Ellingsen

doi:10.1117/12.2293633

Deformable model reconstruction of the subarachnoid space

Jeffrey Glaister, Muhan Shao, Xiang Li, Aaron Carass, Snehashis Roy, Ari M. Blitz, Jerry L. Prince, Lotta M. Ellingsen

Faculty of Electrical and Computer Engineering

University of Iceland

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The subarachnoid space is a layer in the meninges that surrounds the brain and is filled with trabeculae and cerebrospinal fluid. Quantifying the volume and thickness of the subarachnoid space is of interest in order to study the pathogenesis of neurodegenerative diseases and compare with healthy subjects. We present an automatic method to reconstruct the subarachnoid space with subvoxel accuracy using a nested deformable model. The method initializes the deformable model using the convex hull of the union of the outer surfaces of the cerebrum, cerebellum and brainstem. A region force is derived from the subject's T1-weighted and T2-weighted MRI to drive the deformable model to the outer surface of the subarachnoid space. The proposed method is compared to a semi-automatic delineation from the subject's T2-weighted MRI and an existing multi-atlas-based method. A small pilot study comparing the volume and thickness measurements in a set of age-matched subjects with normal pressure hydrocephalus and healthy controls is presented to show the efficacy of the proposed method.

Original language	English
Title of host publication	Medical Imaging 2018
Subtitle of host publication	Image Processing
Editors	Elsa D. Angelini, Bennett A. Landman
Publisher	SPIE
ISBN (Electronic)	9781510616370
DOIs	https://doi.org/10.1117/12.2293633
Publication status	Published - 2018
Event	Medical Imaging 2018: Image Processing - Houston, United States Duration: 11 Feb 2018 → 13 Feb 2018

Publication series

Name	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	10574

Conference

Conference	Medical Imaging 2018: Image Processing
Country/Territory	United States
City	Houston
Period	11/02/18 → 13/02/18

Bibliographical note

Funding Information: This project is funded by the NIH/NINDS through grants R01-NS055951 and R21-NS096497, the Department of Defense in the Center for Neuroscience and Regenerative Medicine, National Multiple Sclerosis Society grant RG-1507-05243, and RANNIS (The Icelandic Centre for Research) grant 173942-051. Publisher Copyright: © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

Other keywords

MRI
deformable models
normal pressure hydrocephalus
subarachnoid space

Access to Document

10.1117/12.2293633

Cite this

Glaister, J., Shao, M., Li, X., Carass, A., Roy, S., Blitz, A. M., Prince, J. L., & Ellingsen, L. M. (2018). Deformable model reconstruction of the subarachnoid space. In E. D. Angelini, & B. A. Landman (Eds.), Medical Imaging 2018: Image Processing Article 1057431 (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 10574). SPIE. https://doi.org/10.1117/12.2293633

@inproceedings{2b3408ee9c644b7da76a89d5aafd11bd,

title = "Deformable model reconstruction of the subarachnoid space",

abstract = "The subarachnoid space is a layer in the meninges that surrounds the brain and is filled with trabeculae and cerebrospinal fluid. Quantifying the volume and thickness of the subarachnoid space is of interest in order to study the pathogenesis of neurodegenerative diseases and compare with healthy subjects. We present an automatic method to reconstruct the subarachnoid space with subvoxel accuracy using a nested deformable model. The method initializes the deformable model using the convex hull of the union of the outer surfaces of the cerebrum, cerebellum and brainstem. A region force is derived from the subject's T1-weighted and T2-weighted MRI to drive the deformable model to the outer surface of the subarachnoid space. The proposed method is compared to a semi-automatic delineation from the subject's T2-weighted MRI and an existing multi-atlas-based method. A small pilot study comparing the volume and thickness measurements in a set of age-matched subjects with normal pressure hydrocephalus and healthy controls is presented to show the efficacy of the proposed method.",

keywords = "MRI, deformable models, normal pressure hydrocephalus, subarachnoid space",

author = "Jeffrey Glaister and Muhan Shao and Xiang Li and Aaron Carass and Snehashis Roy and Blitz, \{Ari M.\} and Prince, \{Jerry L.\} and Ellingsen, \{Lotta M.\}",

note = "Funding Information: This project is funded by the NIH/NINDS through grants R01-NS055951 and R21-NS096497, the Department of Defense in the Center for Neuroscience and Regenerative Medicine, National Multiple Sclerosis Society grant RG-1507-05243, and RANNIS (The Icelandic Centre for Research) grant 173942-051. Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; Medical Imaging 2018: Image Processing ; Conference date: 11-02-2018 Through 13-02-2018",

year = "2018",

doi = "10.1117/12.2293633",

language = "English",

series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",

publisher = "SPIE",

editor = "Angelini, \{Elsa D.\} and Landman, \{Bennett A.\}",

booktitle = "Medical Imaging 2018",

address = "United States",

}

Glaister, J, Shao, M, Li, X, Carass, A, Roy, S, Blitz, AM, Prince, JL & Ellingsen, LM 2018, Deformable model reconstruction of the subarachnoid space. in ED Angelini & BA Landman (eds), Medical Imaging 2018: Image Processing., 1057431, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 10574, SPIE, Medical Imaging 2018: Image Processing, Houston, United States, 11/02/18. https://doi.org/10.1117/12.2293633

Deformable model reconstruction of the subarachnoid space. / Glaister, Jeffrey; Shao, Muhan; Li, Xiang et al.
Medical Imaging 2018: Image Processing. ed. / Elsa D. Angelini; Bennett A. Landman. SPIE, 2018. 1057431 (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 10574).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Deformable model reconstruction of the subarachnoid space

AU - Glaister, Jeffrey

AU - Shao, Muhan

AU - Li, Xiang

AU - Carass, Aaron

AU - Roy, Snehashis

AU - Blitz, Ari M.

AU - Prince, Jerry L.

AU - Ellingsen, Lotta M.

N1 - Funding Information: This project is funded by the NIH/NINDS through grants R01-NS055951 and R21-NS096497, the Department of Defense in the Center for Neuroscience and Regenerative Medicine, National Multiple Sclerosis Society grant RG-1507-05243, and RANNIS (The Icelandic Centre for Research) grant 173942-051. Publisher Copyright: © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

PY - 2018

Y1 - 2018

N2 - The subarachnoid space is a layer in the meninges that surrounds the brain and is filled with trabeculae and cerebrospinal fluid. Quantifying the volume and thickness of the subarachnoid space is of interest in order to study the pathogenesis of neurodegenerative diseases and compare with healthy subjects. We present an automatic method to reconstruct the subarachnoid space with subvoxel accuracy using a nested deformable model. The method initializes the deformable model using the convex hull of the union of the outer surfaces of the cerebrum, cerebellum and brainstem. A region force is derived from the subject's T1-weighted and T2-weighted MRI to drive the deformable model to the outer surface of the subarachnoid space. The proposed method is compared to a semi-automatic delineation from the subject's T2-weighted MRI and an existing multi-atlas-based method. A small pilot study comparing the volume and thickness measurements in a set of age-matched subjects with normal pressure hydrocephalus and healthy controls is presented to show the efficacy of the proposed method.

AB - The subarachnoid space is a layer in the meninges that surrounds the brain and is filled with trabeculae and cerebrospinal fluid. Quantifying the volume and thickness of the subarachnoid space is of interest in order to study the pathogenesis of neurodegenerative diseases and compare with healthy subjects. We present an automatic method to reconstruct the subarachnoid space with subvoxel accuracy using a nested deformable model. The method initializes the deformable model using the convex hull of the union of the outer surfaces of the cerebrum, cerebellum and brainstem. A region force is derived from the subject's T1-weighted and T2-weighted MRI to drive the deformable model to the outer surface of the subarachnoid space. The proposed method is compared to a semi-automatic delineation from the subject's T2-weighted MRI and an existing multi-atlas-based method. A small pilot study comparing the volume and thickness measurements in a set of age-matched subjects with normal pressure hydrocephalus and healthy controls is presented to show the efficacy of the proposed method.

KW - MRI

KW - deformable models

KW - normal pressure hydrocephalus

KW - subarachnoid space

UR - https://www.scopus.com/pages/publications/85047328496

U2 - 10.1117/12.2293633

DO - 10.1117/12.2293633

M3 - Conference contribution

T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE

BT - Medical Imaging 2018

A2 - Angelini, Elsa D.

A2 - Landman, Bennett A.

PB - SPIE

T2 - Medical Imaging 2018: Image Processing

Y2 - 11 February 2018 through 13 February 2018

ER -

Deformable model reconstruction of the subarachnoid space

Abstract

Publication series

Conference

Bibliographical note

Other keywords

Access to Document

Fingerprint

Cite this