title: Morphological image processing for quantitative shape analysis of biomedical structures: effective contrast enhancement.
abstract: Image processing methods significantly contribute to visualization of images captured by biomedical modalities (such as mammography, X-ray computed tomography, magnetic resonance imaging, and light and electron microscopy). Quantitative interpretation of the deluge of complicated biomedical images, however, poses many research challenges, one of which is to enhance structural features that are scarcely perceptible to the human eye. This study introduces a contrast enhancement approach based on a new type of mathematical morphology called rotational morphological processing. The proposed method is applied to medical images for the enhancement of structural features. The effectiveness of the method is evaluated quantitatively by the contrast improvement ratio (CIR). The CIR of the proposed method is 12.1, versus 4.7 and 0.1 for two conventional contrast enhancement methods, clearly indicating the high contrasting capability of the method.
authors.affiliation: Imaging Science Division, Center for Novel Science Initiatives, National Institutes of Natural Sciences, 5-1 Higashiyama, Myodaiji, Okazaki, Aichi 444-8787, Japan.
authors.forename: Yoshitaka
authors.initials: Y
authors.lastname: Kimori
mesh_terms: D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D011856:Radiographic Image Enhancement
keywords: contrast enhancement; image processing; mathematical morphology