eprintid: 11825
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/18/25
datestamp: 2023-11-10 03:26:21
lastmod: 2023-11-10 03:26:21
status_changed: 2023-11-10 01:16:14
type: conference_item
metadata_visibility: show
creators_name: Albashah, N.L.S.B.
creators_name: Asirvadam, V.S.
creators_name: Dass, S.C.
creators_name: Meriaudeau, F.
title: Segmentation of blood clot MRI images using intuitionistic fuzzy set theory
ispublished: pub
keywords: Biomedical engineering; Blood; Fuzzy set theory; Fuzzy sets; Image enhancement; Image fusion; Magnetic resonance imaging; Patient treatment, Dice coefficient; Gradient echo sequences; Intuitionistic fuzzy; Intuitionistic Fuzzy C-Means; Intuitionistic fuzzy sets; Ischemic strokes; Segmentation methods; Segmentation results, Image segmentation
note: cited By 2; Conference of 2018 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2018 ; Conference Date: 3 December 2018 Through 6 December 2018; Conference Code:144644
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. © 2018 IEEE
date: 2019
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062779904&doi=10.1109%2fIECBES.2018.8626678&partnerID=40&md5=fdfadc9690552bbda7dc80f269765911
id_number: 10.1109/IECBES.2018.8626678
full_text_status: none
publication: 2018 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2018 - Proceedings
pagerange: 533-538
refereed: TRUE
isbn: 9781538624715
citation:   Albashah, N.L.S.B. and Asirvadam, V.S. and Dass, S.C. and Meriaudeau, F.  (2019) Segmentation of blood clot MRI images using intuitionistic fuzzy set theory.  In: UNSPECIFIED.