Segmentation of blood clot MRI images using intuitionistic fuzzy set theory
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 us...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2019
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062779904&doi=10.1109%2fIECBES.2018.8626678&partnerID=40&md5=fdfadc9690552bbda7dc80f269765911 http://eprints.utp.edu.my/23544/ |
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| Summary: | 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 |
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