A quantitative method for visual phantom image quality evaluation

Dev Prasad Chakraborty; Xiong Liu; Michael O'Shea; Lawrence C. Toto

doi:10.1117/12.383121

14 April 2000 A quantitative method for visual phantom image quality evaluation

Dev Prasad Chakraborty, Xiong Liu, Michael O'Shea, Lawrence C. Toto

Proceedings Volume 3981, Medical Imaging 2000: Image Perception and Performance; (2000) https://doi.org/10.1117/12.383121
Event: Medical Imaging 2000, 2000, San Diego, CA, United States

Abstract

This work presents an image quality evaluation technique for uniform-background target-object phantom images. The Degradation-Comparison-Threshold (DCT) method involves degrading the image quality of a target-containing region with a blocking processing and comparing the resulting image to a similarly degraded target-free region. The threshold degradation needed for 92% correct detection of the target region is the image quality measure of the target. Images of American College of Radiology (ACR) mammography accreditation program phantom were acquired under varying x-ray conditions on a digital mammography machine. Five observers performed ACR and DCT evaluations of the images. A figure-of-merit (FOM) of an evaluation method was defined which takes into account measurement noise and the change of the measure as a function of x-ray exposure to the phantom. The FOM of the DCT method was 4.1 times that of the ACR method for the specks, 2.7 times better for the fibers and 1.4 times better for the masses. For the specks, inter-reader correlations on the same image set increased significantly from 87% for the ACR method to 97% for the DCT method. The viewing time per target for the DCT method was 3 - 5 minutes. The observed greater sensitivity of the DCT method could lead to more precise Quality Control (QC) testing of digital images, which should improve the sensitivity of the QC process to genuine image quality variations. Another benefit of the method is that it can measure the image quality of high detectability target objects, which is impractical by existing methods.

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Dev Prasad Chakraborty, Xiong Liu, Michael O'Shea, and Lawrence C. Toto "A quantitative method for visual phantom image quality evaluation", Proc. SPIE 3981, Medical Imaging 2000: Image Perception and Performance, (14 April 2000); https://doi.org/10.1117/12.383121

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KEYWORDS

Image quality

Target detection

Image processing

Visualization

Quality measurement

X-rays

Calcium

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