Adaptive Neuro-Fuzzy Inference System for brain abnormality segmentation
This paper studies the application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) for segmentation of brain abnormality in MRI images. Segmentation of MRI image is an important part of brain imaging research. In this study, 150 MRI images were used as testing data for the system. The data was...
| Published in: | Proceedings - ICSGRC 2010: 2010 IEEE Control and System Graduate Research Colloquium |
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| Main Author: | |
| Format: | Conference paper |
| Language: | English |
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2010
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-77958017248&doi=10.1109%2fICSGRC.2010.5562519&partnerID=40&md5=a8ad434e7ffbec2503423fa147b6eda1 |
| Summary: | This paper studies the application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) for segmentation of brain abnormality in MRI images. Segmentation of MRI image is an important part of brain imaging research. In this study, 150 MRI images were used as testing data for the system. The data was created by combining the shapes and size of various abnormalities and pasting it onto normal brain image. Several types of backgrounds were tested - low, medium and high grey levels. The experimental results show good segmentation for medium and low background levels value for both light and dark abnormality levels over different backgrounds. © 2010 IEEE. |
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| DOI: | 10.1109/ICSGRC.2010.5562519 |