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Brain lesion segmentation of diffusion-weighted MRI using thresholding technique

Mohd. Saad, N. and Salahuddin, L. and Syed Abu Bakar, Syed Abdul Rahman and Muda, S. and Mohd. Mokji, Musa (2011) Brain lesion segmentation of diffusion-weighted MRI using thresholding technique. In: 5th Kuala Lumpur International Conference on Biomedical Engineering 2011: (BIOMED 2011) 20-23 June 2011, Kuala Lumpur, Malaysia. IFMBE Proceedings . Springer Berlin Heidelberg, Germany, 604 -610. ISBN 978-364221728-9

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Official URL: http://dx.doi.org/10.1007/978-3-642-21729-6_150


his paper presents brain lesion segmentation of diffusion-weighted magnetic resonance images (DW-MRI or DWI) based on thresholding technique. The lesions are solid tumor, acute infarction, haemorrhage, and abscess. Pre-processing is applied to the DWI for normalization, background removal and enhancement. Two different techniques which are Gamma-law transformation and contrast stretching are applied for the enhancement. For the image segmentation process, the DWI is divided by 8 x 8 regions. Then image histogram is calculated at each region to find the maximum number of pixels for each intensity level. The optimal threshold is determined by comparing normal and lesion regions. By using Gamma-law transformation, 0.48 is found as the optimal thresholding value whereas 0.28 for the contrast stretching. The proposed technique has been validated by using area overlap (AO), false positive rate (FPR), and false negative rate (FNR). Thresholding with gamma-law transformation algorithm provides better segmentation results compared to contrast stretching technique. The proposed technique provides good brain lesion segmentation results even though the simplest segmentation technique is used.

Item Type:Book Section
Uncontrolled Keywords:DWI, gamma-law and contrast stretching, segmentation, thresholding
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:28923
Deposited By: Liza Porijo
Deposited On:04 Dec 2012 04:22
Last Modified:04 Feb 2017 08:33

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