Contrast and Brightness Enhancement for DICOM Images and Lesions Auto Detection

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.

An improved method of image enhancement based on fuzzy theory

“…So image preprocessing methods are needed before target detection. Image enhancement [1][2][3][4][5][6][7] is one of the important techniques in image preprocessing to enhance the image detail and suppress noises. Classic image enhancement technique always simply changes the contrast ratio or suppresses noises of the whole image, while ignoring the ambiguous information of the image.…”