A curvelet-based morphological segmentation of abdominal CT images

M. Sakalli; T. D. Pham; K. M. Lam; H. Yan

doi:10.1109/EMBC.2014.6944882

A curvelet-based morphological segmentation of abdominal CT images

M. Sakalli^*
, T. D. Pham
, K. M. Lam
, H. Yan

^*Corresponding author for this work

Department of Electrical Engineering

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

2 Citations (Scopus)

Abstract

This paper presents a segmentation methodology of abdominal axial CT images. The aim of the study is to determine the location of mesenteric area from the axial images so the organs enclosed within can be localized precisely for diagnostic purposes. The challenge confronted here is that there is no a certain deterministic shape of abdominal organs. The methodology implemented here utilizes a curvelets stage followed by morphological image processing to achieve a contour emphasized segmentation from the gestalts of surrounding organs. This paper gives a detailed analysis of approach taken with the problems faced and a brief comparison wrt to other wavelet approaches.

Original language	English
Title of host publication	2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Publisher	IEEE
Pages	5542-5545
ISBN (Print)	9781424479290
DOIs	https://doi.org/10.1109/EMBC.2014.6944882
Publication status	Published - 2 Nov 2014
Event	36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014) - Sheraton Chicago Hotel and Towers, Chicago, United States Duration: 26 Aug 2014 → 30 Aug 2014 https://www.emedevents.com/c/medical-conferences-2014/36th-annual-international-conference-of-the-ieee-engineering-in-medicine-and-biology-society-embc-2014

Conference

Conference	36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014)
Abbreviated title	EMBC 2014
Place	United States
City	Chicago
Period	26/08/14 → 30/08/14
Internet address	https://www.emedevents.com/c/medical-conferences-2014/36th-annual-international-conference-of-the-ieee-engineering-in-medicine-and-biology-society-embc-2014

Research Keywords

abdominal image segmentation
connected-components labeling
curvelets
edge and contour detection
non-maximal suppression
wavelets

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10.1109/EMBC.2014.6944882

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@inproceedings{990e8be0890347a5bd853a1c8140a0cf,

title = "A curvelet-based morphological segmentation of abdominal CT images",

abstract = "This paper presents a segmentation methodology of abdominal axial CT images. The aim of the study is to determine the location of mesenteric area from the axial images so the organs enclosed within can be localized precisely for diagnostic purposes. The challenge confronted here is that there is no a certain deterministic shape of abdominal organs. The methodology implemented here utilizes a curvelets stage followed by morphological image processing to achieve a contour emphasized segmentation from the gestalts of surrounding organs. This paper gives a detailed analysis of approach taken with the problems faced and a brief comparison wrt to other wavelet approaches.",

keywords = "abdominal image segmentation, connected-components labeling, curvelets, edge and contour detection, non-maximal suppression, wavelets",

author = "M. Sakalli and Pham, \{T. D.\} and Lam, \{K. M.\} and H. Yan",

year = "2014",

month = nov,

day = "2",

doi = "10.1109/EMBC.2014.6944882",

language = "English",

isbn = "9781424479290",

pages = "5542--5545",

booktitle = "2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014",

publisher = "IEEE",

address = "United States",

note = "36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014), EMBC 2014 ; Conference date: 26-08-2014 Through 30-08-2014",

url = "https://www.emedevents.com/c/medical-conferences-2014/36th-annual-international-conference-of-the-ieee-engineering-in-medicine-and-biology-society-embc-2014",

}

Sakalli, M, Pham, TD, Lam, KM & Yan, H 2014, A curvelet-based morphological segmentation of abdominal CT images. in 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014., 6944882, IEEE, pp. 5542-5545, 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014), Chicago, Illinois, United States, 26/08/14. https://doi.org/10.1109/EMBC.2014.6944882

A curvelet-based morphological segmentation of abdominal CT images. / Sakalli, M.; Pham, T. D.; Lam, K. M. et al.
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014. IEEE, 2014. p. 5542-5545 6944882.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - A curvelet-based morphological segmentation of abdominal CT images

AU - Sakalli, M.

AU - Pham, T. D.

AU - Lam, K. M.

AU - Yan, H.

PY - 2014/11/2

Y1 - 2014/11/2

N2 - This paper presents a segmentation methodology of abdominal axial CT images. The aim of the study is to determine the location of mesenteric area from the axial images so the organs enclosed within can be localized precisely for diagnostic purposes. The challenge confronted here is that there is no a certain deterministic shape of abdominal organs. The methodology implemented here utilizes a curvelets stage followed by morphological image processing to achieve a contour emphasized segmentation from the gestalts of surrounding organs. This paper gives a detailed analysis of approach taken with the problems faced and a brief comparison wrt to other wavelet approaches.

AB - This paper presents a segmentation methodology of abdominal axial CT images. The aim of the study is to determine the location of mesenteric area from the axial images so the organs enclosed within can be localized precisely for diagnostic purposes. The challenge confronted here is that there is no a certain deterministic shape of abdominal organs. The methodology implemented here utilizes a curvelets stage followed by morphological image processing to achieve a contour emphasized segmentation from the gestalts of surrounding organs. This paper gives a detailed analysis of approach taken with the problems faced and a brief comparison wrt to other wavelet approaches.

KW - abdominal image segmentation

KW - connected-components labeling

KW - curvelets

KW - edge and contour detection

KW - non-maximal suppression

KW - wavelets

UR - https://www.scopus.com/pages/publications/84929484825

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U2 - 10.1109/EMBC.2014.6944882

DO - 10.1109/EMBC.2014.6944882

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781424479290

SP - 5542

EP - 5545

BT - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014

PB - IEEE

T2 - 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014)

Y2 - 26 August 2014 through 30 August 2014

ER -

A curvelet-based morphological segmentation of abdominal CT images

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