Segmentation of abdominal aortic aneurysm (AAA) based on topology prior model

Safa Salahat; Ahmed Soliman; Tim McGloughlin; Naoufel Werghi; Ayman El-Baz

doi:10.1007/978-3-319-60964-5_19

Segmentation of abdominal aortic aneurysm (AAA) based on topology prior model

Safa Salahat, Ahmed Soliman, Tim McGloughlin, Naoufel Werghi, Ayman El-Baz

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

Abstract

In this paper, we propose a statistical based method using a topology prior model, integrating both intensity and shape information, to segment abdominal aortic aneurysm (AAA) from computed tomography angiography (CTA) scans. The method was tested on a total of 48 slices taken from 6 different patients and has shown competitive performance compared with the best reported results in the literature. Our method has achieved a mean Dice coefficient of 0.9303_±0.0499, and mean Hausdorff distance of 3.5703_±3.1941 mm. This method overcomes the major problem faced by currently existing solutions of similar Hounsfield values of neighboring tissues to that of the AAA thrombus. This is a promising medical tool which can be used to analyze the AAA in order to generate an accurate rupture risk indicator.

Original language	English
Title of host publication	Medical Image Understanding and Analysis - 21st Annual Conference, MIUA 2017, Proceedings
Editors	Victor Gonzalez-Castro, Maria Valdes Hernandez
Publisher	Springer Verlag
Pages	219-228
Number of pages	10
ISBN (Print)	9783319609638
DOIs	https://doi.org/10.1007/978-3-319-60964-5_19
Publication status	Published - 2017
Externally published	Yes
Event	21st Annual Conference on Medical Image Understanding and Analysis, MIUA 2017 - Edinburgh, United Kingdom Duration: 11 Jul 2017 → 13 Jul 2017

Publication series

Name	Communications in Computer and Information Science
Volume	723
ISSN (Print)	1865-0929

Conference

Conference	21st Annual Conference on Medical Image Understanding and Analysis, MIUA 2017
Country/Territory	United Kingdom
City	Edinburgh
Period	11/07/17 → 13/07/17

Keywords

Abdominal aortic aneurysm
Lumen
Probability
Segmentation
Thrombus
Topology

Access to Document

10.1007/978-3-319-60964-5_19

Cite this

Salahat, S., Soliman, A., McGloughlin, T., Werghi, N., & El-Baz, A. (2017). Segmentation of abdominal aortic aneurysm (AAA) based on topology prior model. In V. Gonzalez-Castro, & M. Valdes Hernandez (Eds.), Medical Image Understanding and Analysis - 21st Annual Conference, MIUA 2017, Proceedings (pp. 219-228). (Communications in Computer and Information Science; Vol. 723). Springer Verlag. https://doi.org/10.1007/978-3-319-60964-5_19

Salahat, Safa ; Soliman, Ahmed ; McGloughlin, Tim et al. / Segmentation of abdominal aortic aneurysm (AAA) based on topology prior model. Medical Image Understanding and Analysis - 21st Annual Conference, MIUA 2017, Proceedings. editor / Victor Gonzalez-Castro ; Maria Valdes Hernandez. Springer Verlag, 2017. pp. 219-228 (Communications in Computer and Information Science).

@inproceedings{de1639388cfe449eb712f5c7d68de2cf,

title = "Segmentation of abdominal aortic aneurysm (AAA) based on topology prior model",

abstract = "In this paper, we propose a statistical based method using a topology prior model, integrating both intensity and shape information, to segment abdominal aortic aneurysm (AAA) from computed tomography angiography (CTA) scans. The method was tested on a total of 48 slices taken from 6 different patients and has shown competitive performance compared with the best reported results in the literature. Our method has achieved a mean Dice coefficient of 0.9303±0.0499, and mean Hausdorff distance of 3.5703±3.1941 mm. This method overcomes the major problem faced by currently existing solutions of similar Hounsfield values of neighboring tissues to that of the AAA thrombus. This is a promising medical tool which can be used to analyze the AAA in order to generate an accurate rupture risk indicator.",

keywords = "Abdominal aortic aneurysm, Lumen, Probability, Segmentation, Thrombus, Topology",

author = "Safa Salahat and Ahmed Soliman and Tim McGloughlin and Naoufel Werghi and Ayman El-Baz",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 21st Annual Conference on Medical Image Understanding and Analysis, MIUA 2017 ; Conference date: 11-07-2017 Through 13-07-2017",

year = "2017",

doi = "10.1007/978-3-319-60964-5_19",

language = "English",

isbn = "9783319609638",

series = "Communications in Computer and Information Science",

publisher = "Springer Verlag",

pages = "219--228",

editor = "Victor Gonzalez-Castro and {Valdes Hernandez}, Maria",

booktitle = "Medical Image Understanding and Analysis - 21st Annual Conference, MIUA 2017, Proceedings",

}

Salahat, S, Soliman, A, McGloughlin, T, Werghi, N & El-Baz, A 2017, Segmentation of abdominal aortic aneurysm (AAA) based on topology prior model. in V Gonzalez-Castro & M Valdes Hernandez (eds), Medical Image Understanding and Analysis - 21st Annual Conference, MIUA 2017, Proceedings. Communications in Computer and Information Science, vol. 723, Springer Verlag, pp. 219-228, 21st Annual Conference on Medical Image Understanding and Analysis, MIUA 2017, Edinburgh, United Kingdom, 11/07/17. https://doi.org/10.1007/978-3-319-60964-5_19

Segmentation of abdominal aortic aneurysm (AAA) based on topology prior model. / Salahat, Safa; Soliman, Ahmed; McGloughlin, Tim et al.
Medical Image Understanding and Analysis - 21st Annual Conference, MIUA 2017, Proceedings. ed. / Victor Gonzalez-Castro; Maria Valdes Hernandez. Springer Verlag, 2017. p. 219-228 (Communications in Computer and Information Science; Vol. 723).

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

TY - GEN

T1 - Segmentation of abdominal aortic aneurysm (AAA) based on topology prior model

AU - Salahat, Safa

AU - Soliman, Ahmed

AU - McGloughlin, Tim

AU - Werghi, Naoufel

AU - El-Baz, Ayman

N1 - Publisher Copyright: © Springer International Publishing AG 2017.

PY - 2017

Y1 - 2017

N2 - In this paper, we propose a statistical based method using a topology prior model, integrating both intensity and shape information, to segment abdominal aortic aneurysm (AAA) from computed tomography angiography (CTA) scans. The method was tested on a total of 48 slices taken from 6 different patients and has shown competitive performance compared with the best reported results in the literature. Our method has achieved a mean Dice coefficient of 0.9303±0.0499, and mean Hausdorff distance of 3.5703±3.1941 mm. This method overcomes the major problem faced by currently existing solutions of similar Hounsfield values of neighboring tissues to that of the AAA thrombus. This is a promising medical tool which can be used to analyze the AAA in order to generate an accurate rupture risk indicator.

AB - In this paper, we propose a statistical based method using a topology prior model, integrating both intensity and shape information, to segment abdominal aortic aneurysm (AAA) from computed tomography angiography (CTA) scans. The method was tested on a total of 48 slices taken from 6 different patients and has shown competitive performance compared with the best reported results in the literature. Our method has achieved a mean Dice coefficient of 0.9303±0.0499, and mean Hausdorff distance of 3.5703±3.1941 mm. This method overcomes the major problem faced by currently existing solutions of similar Hounsfield values of neighboring tissues to that of the AAA thrombus. This is a promising medical tool which can be used to analyze the AAA in order to generate an accurate rupture risk indicator.

KW - Abdominal aortic aneurysm

KW - Lumen

KW - Probability

KW - Segmentation

KW - Thrombus

KW - Topology

UR - http://www.scopus.com/inward/record.url?scp=85022221493&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-60964-5_19

DO - 10.1007/978-3-319-60964-5_19

M3 - Conference contribution

AN - SCOPUS:85022221493

SN - 9783319609638

T3 - Communications in Computer and Information Science

SP - 219

EP - 228

BT - Medical Image Understanding and Analysis - 21st Annual Conference, MIUA 2017, Proceedings

A2 - Gonzalez-Castro, Victor

A2 - Valdes Hernandez, Maria

PB - Springer Verlag

T2 - 21st Annual Conference on Medical Image Understanding and Analysis, MIUA 2017

Y2 - 11 July 2017 through 13 July 2017

ER -

Salahat S, Soliman A, McGloughlin T, Werghi N, El-Baz A. Segmentation of abdominal aortic aneurysm (AAA) based on topology prior model. In Gonzalez-Castro V, Valdes Hernandez M, editors, Medical Image Understanding and Analysis - 21st Annual Conference, MIUA 2017, Proceedings. Springer Verlag. 2017. p. 219-228. (Communications in Computer and Information Science). doi: 10.1007/978-3-319-60964-5_19

Segmentation of abdominal aortic aneurysm (AAA) based on topology prior model

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this