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Contrast and Brightness Enhancement for DICOM Images and Lesions Auto Detection

Chin Jie Lew, Kok Swee Sim, and Teck Kiang Kho
Faculty of Engineering and Technology, Multimedia University, Jalan Ayer Keroh Lama, 75450, Melaka, Malaysia

Abstract—Brain lesions can cause severe dysfunction of the human body, and mind. It may result in fatality if it is not detected early. This paper focuses on the detection of lesions through image processing. Three different approaches are proposed to detect ischemic infarct. The detection of hemorrhagic infarct is done automatically with windowing DICOM images by setting optimal window width and window centre and then the lesion area is found by using human observation, database matching and saturation level detection method. This paper is mainly about way of aiding human to analyses lesion in CT Scan by finding the best windows setting and filter out the unnecessary information in DICOM images. The filtered images are applied with contrast enhancement to make observation and confirmation process easier and more accurate. The possible lesion areas are plotted with mark by human. After that the result is double confirmed with auto detection by computer.

Index Terms—DICOM, histogram equalization, HE, sub-block, contrast, brightness, image processing, lesion

Cite: Chin Jie Lew, Kok Swee Sim, and Teck Kiang Kho, "Contrast and Brightness Enhancement for DICOM Images and Lesions Auto Detection," Journal of Image and Graphics, Vol. 4, No. 1, pp. 25-28, June 2016. doi: 10.18178/joig.4.1.25-28

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