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A Mutual Information-Based Image Quality Metric for Medical Imaging Systems
Author(s) -
DuYih Tsai,
Eri Matsuyama,
Yongbum Lee
Publication year - 2011
Publication title -
intech ebooks
Language(s) - English
Resource type - Book series
DOI - 10.5772/26384
Subject(s) - mutual information , computer science , metric (unit) , image quality , quality (philosophy) , artificial intelligence , computer vision , medical information , image (mathematics) , medical imaging , information retrieval , engineering , physics , operations management , quantum mechanics
Information on physical image quality of medical images is important for imaging system assessment in order to promote and stimulate the development of state-of-the-art imaging systems. In this chapter, we present a method for quantifying overall image quality of digital imaging systems using mutual information (MI) metric. The MI which is a concept from information theory is used as a measure to express the amount of information that an output image contains about an input object. The MI value is considered that it can be used to express combined physical properties of image noise, resolution and contrast of an imaging system. The higher the MI value, the better the image quality. The advantages of using the MI metric are: (1) simplicity of computation, (2) simplicity of experimentation, and (3) combined assessment of image contrast, noise and resolution.

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