Open AccessMorphological image processing for quantitative shape analysis of biomedical structures: effective contrast enhancement
Author(s) -
Kimori Yoshitaka
Publication year - 2013
Publication title -
journal of synchrotron radiation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.172
H-Index - 99
ISSN - 1600-5775
DOI - 10.1107/s0909049513020761
Subject(s) - contrast (vision) , visualization , contrast enhancement , computer science , artificial intelligence , image processing , image contrast , medical imaging , computer vision , image enhancement , magnetic resonance imaging , materials science , biomedical engineering , image (mathematics) , medicine , radiology
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.