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2016 | OriginalPaper | Chapter

Model-Based Fuzzy System for Multimodal Image Segmentation

Author : Joanna Czajkowska

Published in: Computational Intelligence

Publisher: Springer International Publishing

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Abstract

In this paper, a new model-based fuzzy system for multimodal 3-D image segmentation in MR series is introduced. The presented fuzzy system calculates affinity values for fuzzy connectedness segmentation procedure, which is the main stage of the processing. The fuzzy rules, generated for the system simulating a radiological analysis, are structured on the basis of Gaussian mixture model of analyzed image regions. For the model parameters estimation, different MR modalities, acquired during a single examination, are used. The segmentation abilities of a prototype system have been tested on two medical databases. The first one consists of 27 examinations with bone tumors, which are visualized with two different MR sequences. The second one is the database of brain tumors with ground truth description obtained from the MICCAI 2012 Challenge on Multimodal Brain Tumor Segmentation.

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previous chapter A Hybrid Shuffled Frog-Leaping Algorithm for the University Examination Timetabling Problem
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Metadata
Title
Model-Based Fuzzy System for Multimodal Image Segmentation
Author
Joanna Czajkowska
Copyright Year
2016
Book
Computational Intelligence

Print ISBN: 978-3-319-23391-8

Electronic ISBN: 978-3-319-23392-5

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-23392-5_11

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