Segmenting crossing fiber geometries using fluid mechanics tensor distribution function tractography

Nathan Hageman; Alex Leow; David Shattuck; Liang Zhan; Paul Thompson; Siwei Zhu; Arthur Toga

doi:10.1109/ISBI.2009.5193325

Segmenting crossing fiber geometries using fluid mechanics tensor distribution function tractography

Nathan Hageman
, Alex Leow
, David Shattuck
, Liang Zhan
, Paul Thompson
, Siwei Zhu
, Arthur Toga

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

Abstract

We introduce a fluid mechanics based tractography method that estimates the most likely connection path between points in a tensor distribution function (TDF) dataset. We simulated the flow of an artificial fluid whose properties are related to the underlying TDF dataset. The resulting fluid velocity was used as a metric of connection strength. We validated our algorithm using a digital phantom dataset based on a pattern with two intersecting tracts. When compared to a TDF streamline method and our single tensor fluid mechanics tractography algorithm, our method was able to segment intersecting tracts at a finer spatial resolution. Our method was successfully applied to human control data to segment a major fiber pathway, the corpus callosum, even in problematic regions with crossing fiber geometries.

Original language	English
Title of host publication	Proceedings - 2009 IEEE International Symposium on Biomedical Imaging
Subtitle of host publication	From Nano to Macro, ISBI 2009
Publisher	IEEE Computer Society
Pages	1390-1393
Number of pages	4
ISBN (Print)	9781424439324
DOIs	https://doi.org/10.1109/ISBI.2009.5193325
State	Published - 2009
Externally published	Yes
Event	6th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009 - Boston, MA, United States Duration: 28 Jun 2009 → 1 Jul 2009

Publication series

Name	Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009

Conference

Conference	6th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009
Country/Territory	United States
City	Boston, MA
Period	28/06/09 → 1/07/09

Keywords

Biomedical image processing
Fluid flow
Image segmentation
Magnetic resonance imaging
Partial differential equations

Access to Document

10.1109/ISBI.2009.5193325

Cite this

Hageman, N., Leow, A., Shattuck, D., Zhan, L., Thompson, P., Zhu, S., & Toga, A. (2009). Segmenting crossing fiber geometries using fluid mechanics tensor distribution function tractography. In Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009 (pp. 1390-1393). Article 5193325 (Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009). IEEE Computer Society. https://doi.org/10.1109/ISBI.2009.5193325

Hageman, Nathan ; Leow, Alex ; Shattuck, David et al. / Segmenting crossing fiber geometries using fluid mechanics tensor distribution function tractography. Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009. IEEE Computer Society, 2009. pp. 1390-1393 (Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009).

@inproceedings{7faaf44c9d8c4ef9a3e0069910aee5e2,

title = "Segmenting crossing fiber geometries using fluid mechanics tensor distribution function tractography",

abstract = "We introduce a fluid mechanics based tractography method that estimates the most likely connection path between points in a tensor distribution function (TDF) dataset. We simulated the flow of an artificial fluid whose properties are related to the underlying TDF dataset. The resulting fluid velocity was used as a metric of connection strength. We validated our algorithm using a digital phantom dataset based on a pattern with two intersecting tracts. When compared to a TDF streamline method and our single tensor fluid mechanics tractography algorithm, our method was able to segment intersecting tracts at a finer spatial resolution. Our method was successfully applied to human control data to segment a major fiber pathway, the corpus callosum, even in problematic regions with crossing fiber geometries.",

keywords = "Biomedical image processing, Fluid flow, Image segmentation, Magnetic resonance imaging, Partial differential equations",

author = "Nathan Hageman and Alex Leow and David Shattuck and Liang Zhan and Paul Thompson and Siwei Zhu and Arthur Toga",

year = "2009",

doi = "10.1109/ISBI.2009.5193325",

language = "English",

isbn = "9781424439324",

series = "Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009",

publisher = "IEEE Computer Society",

pages = "1390--1393",

booktitle = "Proceedings - 2009 IEEE International Symposium on Biomedical Imaging",

address = "United States",

note = "6th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009 ; Conference date: 28-06-2009 Through 01-07-2009",

}

Hageman, N, Leow, A, Shattuck, D, Zhan, L, Thompson, P, Zhu, S & Toga, A 2009, Segmenting crossing fiber geometries using fluid mechanics tensor distribution function tractography. in Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009., 5193325, Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009, IEEE Computer Society, pp. 1390-1393, 6th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009, Boston, MA, United States, 28/06/09. https://doi.org/10.1109/ISBI.2009.5193325

Segmenting crossing fiber geometries using fluid mechanics tensor distribution function tractography. / Hageman, Nathan; Leow, Alex; Shattuck, David et al.
Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009. IEEE Computer Society, 2009. p. 1390-1393 5193325 (Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009).

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

TY - GEN

T1 - Segmenting crossing fiber geometries using fluid mechanics tensor distribution function tractography

AU - Hageman, Nathan

AU - Leow, Alex

AU - Shattuck, David

AU - Zhan, Liang

AU - Thompson, Paul

AU - Zhu, Siwei

AU - Toga, Arthur

PY - 2009

Y1 - 2009

N2 - We introduce a fluid mechanics based tractography method that estimates the most likely connection path between points in a tensor distribution function (TDF) dataset. We simulated the flow of an artificial fluid whose properties are related to the underlying TDF dataset. The resulting fluid velocity was used as a metric of connection strength. We validated our algorithm using a digital phantom dataset based on a pattern with two intersecting tracts. When compared to a TDF streamline method and our single tensor fluid mechanics tractography algorithm, our method was able to segment intersecting tracts at a finer spatial resolution. Our method was successfully applied to human control data to segment a major fiber pathway, the corpus callosum, even in problematic regions with crossing fiber geometries.

AB - We introduce a fluid mechanics based tractography method that estimates the most likely connection path between points in a tensor distribution function (TDF) dataset. We simulated the flow of an artificial fluid whose properties are related to the underlying TDF dataset. The resulting fluid velocity was used as a metric of connection strength. We validated our algorithm using a digital phantom dataset based on a pattern with two intersecting tracts. When compared to a TDF streamline method and our single tensor fluid mechanics tractography algorithm, our method was able to segment intersecting tracts at a finer spatial resolution. Our method was successfully applied to human control data to segment a major fiber pathway, the corpus callosum, even in problematic regions with crossing fiber geometries.

KW - Biomedical image processing

KW - Fluid flow

KW - Image segmentation

KW - Magnetic resonance imaging

KW - Partial differential equations

UR - https://www.scopus.com/pages/publications/70449435212

U2 - 10.1109/ISBI.2009.5193325

DO - 10.1109/ISBI.2009.5193325

M3 - Conference contribution

AN - SCOPUS:70449435212

SN - 9781424439324

T3 - Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009

SP - 1390

EP - 1393

BT - Proceedings - 2009 IEEE International Symposium on Biomedical Imaging

PB - IEEE Computer Society

T2 - 6th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009

Y2 - 28 June 2009 through 1 July 2009

ER -

Hageman N, Leow A, Shattuck D, Zhan L, Thompson P, Zhu S et al. Segmenting crossing fiber geometries using fluid mechanics tensor distribution function tractography. In Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009. IEEE Computer Society. 2009. p. 1390-1393. 5193325. (Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009). doi: 10.1109/ISBI.2009.5193325

Segmenting crossing fiber geometries using fluid mechanics tensor distribution function tractography

Abstract

Publication series

Conference

Keywords

Access to Document

Fingerprint

Cite this