標題: Correction of inhomogeneous magnetic resonance images using multiscale retinex for segmentation accuracy improvement
作者: Chao, Wen-Hung
Lai, Hsin-Yi
Shih, Yen-Yu I.
Chen, You-Yin
Lo, Yu-Chun
Lin, Sheng-Huang
Tsang, Siny
Wu, Robby
Jaw, Fu-Shan
電機工程學系
Department of Electrical and Computer Engineering
關鍵字: Segmentation;Boosted decision tree;Multiscale retinex;Spatial feature;Brain tissue
公開日期: 1-Mar-2012
摘要: The purpose of this study was to improve the accuracy of tissue segmentation on brain magnetic resonance (MR) images preprocessed by multiscale retinex (MSR), segmented with a combined boosted decision tree (BDT) and MSR algorithm (hereinafter referred to as the MSRBDT algorithm). Simulated brain MR (SBMR) T1-weighted images of different noise levels and RF inhomogeneities were adopted to evaluate the outcome of the proposed method; the MSRBDT algorithm was used to identify the gray matter (GM), white matter (WM), and cerebral-spinal fluid (CSF) in the brain tissues. The accuracy rates of GM, WM, and CSF segmentation, with spatial features (G, x, y, r, theta), were respectively greater than 0.9805, 0.9817, and 0.9871. In addition, images segmented with the MSRBDT algorithm were better than those obtained with the expectation maximization (EM) algorithm; brain tissue segmentation in MR images was significantly more precise. The proposed MSRBDT algorithm could be beneficial in clinical image segmentation. (C) 2011 Elsevier Ltd. All rights reserved.
URI: http://dx.doi.org/10.1016/j.bspc.2011.04.001
http://hdl.handle.net/11536/15831
ISSN: 1746-8094
DOI: 10.1016/j.bspc.2011.04.001
期刊: BIOMEDICAL SIGNAL PROCESSING AND CONTROL
Volume: 7
Issue: 2
起始頁: 129
結束頁: 140
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