Quantification of radiographic image quality based on patient anatomical contrast-to-noise ratio: a preliminary study with chest images

Yuan Lin; Xiaohui Wang; William J. Sehnert; David H. Foos; Lori Barski; Ehsan Samei

doi:10.1117/12.847033

3 March 2010 Quantification of radiographic image quality based on patient anatomical contrast-to-noise ratio: a preliminary study with chest images

Yuan Lin, Xiaohui Wang, William J. Sehnert, David H. Foos, Lori Barski, Ehsan Samei

Author Affiliations +

Proceedings Volume 7627, Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment; 76271F (2010) https://doi.org/10.1117/12.847033
Event: SPIE Medical Imaging, 2010, San Diego, California, United States

Abstract

The quality of a digital radiograph for diagnostic imaging depends on many factors, such as the capture system DQE and MTF, the exposure technique factors, the patient anatomy, and the particular image processing method and processing parameters used. Therefore, the overall image quality as perceived by the radiologists depends on many factors. This work explores objective image quality metrics directly from display-ready patient images. A preliminary study was conducted based on a multi-frequency analysis of anatomy contrast and noise magnitude from 250 computed radiography (CR) chest radiographs (150 PA, 50 AP captured with anti-scatter grids, and 50 AP without grids). The contrast and noise values were evaluated in different sub-bands separately according to their frequency properties. Contrast-Noise ratio (CNR) was calculated, the results correlated well with the human observers' overall impression on the images captured with and without grids.

Citation Download Citation

Yuan Lin, Xiaohui Wang, William J. Sehnert, David H. Foos, Lori Barski, and Ehsan Samei "Quantification of radiographic image quality based on patient anatomical contrast-to-noise ratio: a preliminary study with chest images", Proc. SPIE 7627, Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment, 76271F (3 March 2010); https://doi.org/10.1117/12.847033

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