Segmentation Of Blood Clot MRI Images Using Intuitionistic Fuzzy Set Theory

Nur Lyana Shahfiqa Binti Albashah; Sarat Chandra Dass; Vijanth Sagayan Asirvadam; Fabrice Meriaudeau

doi:10.1109/IECBES.2018.8626678

Segmentation Of Blood Clot MRI Images Using Intuitionistic Fuzzy Set Theory

Nur Lyana Shahfiqa Binti Albashah, Sarat Chandra Dass, Vijanth Sagayan Asirvadam, Fabrice Meriaudeau

School of Mathematical & Computer Sciences

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

3 Citations (Scopus)

Abstract

This paper presents the segmentation method to differentiate between hard and soft clot regions of blood clots in ischemic stroke patients. This is important in planning treatment options for stroke patients as the nature of the clot determines the type of treatment. The gradient echo sequence is used to produce MRI datasets. The MRI blood clot image consists of hard and soft clot regions which have different intensity values. However, the blood clot regions are adjacent to each other, not homogeneous and have unclear boundaries which are the main problems when segmenting the regions. Intuitionistic fuzzy fusion methodology is used to help enhance the noisy image and is shown to lead good segmentation result while using the spatial version of intuitionistic fuzzy c-mean clustering with dice coefficient of 0.8270 and 0.819 for hard clot region and soft clot region respectively.

Original language	English
Title of host publication	2018 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)
Publisher	IEEE
Pages	533-538
Number of pages	6
ISBN (Electronic)	9781538624715
DOIs	https://doi.org/10.1109/IECBES.2018.8626678
Publication status	Published - 27 Jan 2019
Event	2018 IEEE EMBS Conference on Biomedical Engineering and Sciences - Sarawak, Malaysia Duration: 3 Dec 2018 → 6 Dec 2018

Conference

Conference	2018 IEEE EMBS Conference on Biomedical Engineering and Sciences
Abbreviated title	IECBES 2018
Country/Territory	Malaysia
City	Sarawak
Period	3/12/18 → 6/12/18

Keywords

Image fusion
Image segmentation
Intuitionistic fuzzy set
Ischemic stroke

ASJC Scopus subject areas

Biomedical Engineering
Medicine (miscellaneous)
Health Informatics
Instrumentation

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10.1109/IECBES.2018.8626678

Cite this

@inproceedings{6cb68e32507645a2aa2a984cc0836363,

title = "Segmentation Of Blood Clot MRI Images Using Intuitionistic Fuzzy Set Theory",

abstract = "This paper presents the segmentation method to differentiate between hard and soft clot regions of blood clots in ischemic stroke patients. This is important in planning treatment options for stroke patients as the nature of the clot determines the type of treatment. The gradient echo sequence is used to produce MRI datasets. The MRI blood clot image consists of hard and soft clot regions which have different intensity values. However, the blood clot regions are adjacent to each other, not homogeneous and have unclear boundaries which are the main problems when segmenting the regions. Intuitionistic fuzzy fusion methodology is used to help enhance the noisy image and is shown to lead good segmentation result while using the spatial version of intuitionistic fuzzy c-mean clustering with dice coefficient of 0.8270 and 0.819 for hard clot region and soft clot region respectively.",

keywords = "Image fusion, Image segmentation, Intuitionistic fuzzy set, Ischemic stroke",

author = "Albashah, {Nur Lyana Shahfiqa Binti} and Dass, {Sarat Chandra} and Asirvadam, {Vijanth Sagayan} and Fabrice Meriaudeau",

year = "2019",

month = jan,

day = "27",

doi = "10.1109/IECBES.2018.8626678",

language = "English",

pages = "533--538",

booktitle = "2018 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)",

publisher = "IEEE",

address = "United States",

note = "2018 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2018 ; Conference date: 03-12-2018 Through 06-12-2018",

}

Albashah, NLSB, Dass, SC, Asirvadam, VS & Meriaudeau, F 2019, Segmentation Of Blood Clot MRI Images Using Intuitionistic Fuzzy Set Theory. in 2018 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES). IEEE, pp. 533-538, 2018 IEEE EMBS Conference on Biomedical Engineering and Sciences, Sarawak, Malaysia, 3/12/18. https://doi.org/10.1109/IECBES.2018.8626678

TY - GEN

T1 - Segmentation Of Blood Clot MRI Images Using Intuitionistic Fuzzy Set Theory

AU - Albashah, Nur Lyana Shahfiqa Binti

AU - Dass, Sarat Chandra

AU - Asirvadam, Vijanth Sagayan

AU - Meriaudeau, Fabrice

PY - 2019/1/27

Y1 - 2019/1/27

N2 - This paper presents the segmentation method to differentiate between hard and soft clot regions of blood clots in ischemic stroke patients. This is important in planning treatment options for stroke patients as the nature of the clot determines the type of treatment. The gradient echo sequence is used to produce MRI datasets. The MRI blood clot image consists of hard and soft clot regions which have different intensity values. However, the blood clot regions are adjacent to each other, not homogeneous and have unclear boundaries which are the main problems when segmenting the regions. Intuitionistic fuzzy fusion methodology is used to help enhance the noisy image and is shown to lead good segmentation result while using the spatial version of intuitionistic fuzzy c-mean clustering with dice coefficient of 0.8270 and 0.819 for hard clot region and soft clot region respectively.

AB - This paper presents the segmentation method to differentiate between hard and soft clot regions of blood clots in ischemic stroke patients. This is important in planning treatment options for stroke patients as the nature of the clot determines the type of treatment. The gradient echo sequence is used to produce MRI datasets. The MRI blood clot image consists of hard and soft clot regions which have different intensity values. However, the blood clot regions are adjacent to each other, not homogeneous and have unclear boundaries which are the main problems when segmenting the regions. Intuitionistic fuzzy fusion methodology is used to help enhance the noisy image and is shown to lead good segmentation result while using the spatial version of intuitionistic fuzzy c-mean clustering with dice coefficient of 0.8270 and 0.819 for hard clot region and soft clot region respectively.

KW - Image fusion

KW - Image segmentation

KW - Intuitionistic fuzzy set

KW - Ischemic stroke

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U2 - 10.1109/IECBES.2018.8626678

DO - 10.1109/IECBES.2018.8626678

M3 - Conference contribution

SP - 533

EP - 538

BT - 2018 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)

PB - IEEE

T2 - 2018 IEEE EMBS Conference on Biomedical Engineering and Sciences

Y2 - 3 December 2018 through 6 December 2018

ER -

Segmentation Of Blood Clot MRI Images Using Intuitionistic Fuzzy Set Theory

Abstract

Conference

Keywords

ASJC Scopus subject areas

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