Image Enhancement based Improved Multi-scale Hessian Matrix for Coronary Angiography
Author(s) -
Kaifeng Chen,
Qingbo Yin,
Xiao Jia,
Mingyu Lu
Publication year - 2015
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2015906196
Subject(s) - hessian matrix , computer science , noise (video) , coronary angiography , scale (ratio) , matrix (chemical analysis) , artificial intelligence , angiography , computer vision , image (mathematics) , pattern recognition (psychology) , radiology , medicine , cardiology , mathematics , materials science , physics , composite material , myocardial infarction , quantum mechanics
The coronary angiography image is easy to be affected by many factors, such as vascular thickness varied huge, complex background noise, uneven illumination intensity and so on. The coronary angiography image is more difficult to deal with compared with other similar medical images. By using Hessian matrix multi-scale vascular detection method, the vicinity of blood vessels will yield a lot of background noise, and the small tiny blood vessels become blurred or even lost, which seriously affect the experiment results. In this paper, an improved multi-scale Hessian matrix is presented, combined with morphological top-hat operation for the detection of coronary angiography. The experimental results demonstrate the effectiveness of the proposed method.
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