Ms. Zhengjia Wang Profile

Zhengjia Wang

at Institute for Infocomm Research

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Proceedings Article | 30 April 2004 Paper

Rapid and automatic detection of brain tumors in MR images

Zhengjia Wang, Qingmao Hu, KiaFock Loe, Aamer Aziz, Wieslaw Nowinski

Proceedings Volume 5369, (2004) https://doi.org/10.1117/12.538035

KEYWORDS: Tumors, Brain, Image segmentation, Neuroimaging, Magnetic resonance imaging, Image processing, 3D image processing, Error analysis, Tissues, Algorithm development

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An algorithm to automatically detect brain tumors in MR images is presented. The key concern is speed in order to process efficiently large brain image databases and provide quick outcomes in clinical setting. The method is based on study of asymmetry of the brain. Tumors cause asymmetry of the brain, so we detect brain tumors in 3D MR images using symmetry analysis of image grey levels with respect to the midsagittal plane (MSP). The MSP, separating the brain into two hemispheres, is extracted using our previously developed algorithm. By removing the background pixels, the normalized grey level histograms are calculated for both hemispheres. The similarity between these two histograms manifests the symmetry of the brain, and it is quantified by using four symmetry measures: correlation coefficient, root mean square error, integral of absolute difference (IAD), and integral of normalized absolute difference (INAD). A quantitative analysis of brain normality based on 42 patients with tumors and 55 normals is presented. The sensitivity and specificity of IAD and INAD were 83.3% and 89.1%, and 85.7% and 83.6%, respectively. The running time for each symmetry measure for a 3D 8bit MR data was between 0.1 - 0.3 seconds on a 2.4GHz CPU PC.

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