Muda, A. F. and Saad, N. M. and Abu Bakar, S. A. R. and Muda, S. and Abdullah, A. R. (2015) Brain lesion segmentation using fuzzy C-means on diffusion-weighted imaging. Arpn Journal Of Engineering And Applied Sciences, 10 (3). pp. 1138-1144. ISSN 1819-6608
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Official URL: http://www.arpnjournals.com/jeas/research_papers/r...
Abstract
This paper presents an automatic segmentation of brain lesions from diffusion-weighted imaging (DWI) usingFuzzy C-Means (FCM) algorithm. The lesions are acute stroke, tumour and chronic stroke. Pre-processing is applied to theDWI for intensity normalization, background removal and enhancement. After that, FCM is used for the segmentationprocess. FCM is an iterative process, where the process will stop when the maximum number of iterations is reached or theiteration is repeated until a set point known as the threshold is reached. The FCM provides good segmentation result inhyperintensity and hypointensity lesions according to the high value of the area overlap, and low value of false positive andfalse negative rates. The average dice indices are 0.73(acute stroke), 0.68 (tumour) and 0.82 (chronic stroke).
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | brain lesion, diffusion-weighted imaging, fuzzy c-means |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Electrical Engineering |
| ID Code: | 57977 |
| Deposited By: | Haliza Zainal |
| Deposited On: | 04 Dec 2016 04:07 |
| Last Modified: | 28 Oct 2021 07:01 |
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