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Perceptual quality assessment of medical images

Liu, Hantao and Wang, Zhou 2017. Perceptual quality assessment of medical images. In: Caplan, Michael ed. Reference Module in Biomedical Sciences, Elsevier, (10.1016/B978-0-12-801238-3.64099-0)

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Abstract

Today, healthcare professionals are viewing medical images in a variety of environments. The technologies and methodologies used to acquire, process, store, transmit, and display images vary, and consequently, the ultimate visual information received by the clinicians differs significantly in perceived quality. Visual signal distortions, such as various types of noise and artifacts arising in medical image acquisition, processing, compression, and transmission, affect the perceptual quality of images and potentially impact diagnoses. To optimize clinical practice, we need to understand human perception of medical image quality in practical settings and then use what is learned to develop useful solutions for improved image quality and better image-based diagnoses. This article focuses on the methodologies used to measure the perceptual quality of medical images using magnetic resonance image acquisition and computed tomography image compression as examples, where modern digital image processing technologies and statistical analysis approaches play important roles in helping with both subjective visual testing and objective quality predictions.

Item Type: Book Section
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Publisher: Elsevier
ISBN: 9780128012383
Last Modified: 26 Apr 2018 15:00
URI: http://orca.cf.ac.uk/id/eprint/110837

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