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. 2011 Apr;24(2):331-8.
doi: 10.1007/s10278-009-9268-7.

Influence of image metrics when assessing image quality from a test object in cardiac X-ray systems

Eliseo Vano  1 , Carlos Ubeda, Bernhard Geiger, Luis C Martinez, Stephen Balter
Affiliations

Influence of image metrics when assessing image quality from a test object in cardiac X-ray systems

Eliseo Vano et al. J Digit Imaging. 2011 Apr.

Abstract

Modern fluoroscopic systems used for invasive cardiology typically acquire digital images in a 1,024 × 1,024 × 12 bits. These images are maintained in the original format while they remain on the imaging system itself. However, images are usually stored using a reduced 512 × 512 × 8-bits format. This paper presents a method for digital analysis of test objects images. The results obtained using image-intensifier and flat-detector systems are given for the original and reduced matrices. Images were acquired using a test object (TO) and a range of polymethyl methacrylate (PMMA) thicknesses from 4 to 28 cm. Adult patient protocols were evaluated for 16-28 cm of PMMA using the image-intensifier system. Pediatric protocols were evaluated for 4-16 cm of PMMA using the flat-detector system. The TO contains disks of various thicknesses to evaluate low contrast sensitivity and a bar pattern to evaluate high-contrast spatial resolution (HCSR). All available fluoroscopic and cine modes were evaluated. Entrance surface air kerma was also measured. Signal-to-noise ratio (SNR) was evaluated using regions of interest (ROI). HCSR was evaluated by comparing the statistical analysis of a ROI placed over the image of the bar pattern against a reference ROI. For both systems, an improvement of approximately 20% was observed for the SNR on the reduced matrices. However, the HCSR parameter was substantially lower in the reduced metrics. Cardiologists should consider the clinical influence of reduced spatial resolution when using the archived images.

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Figures

Fig 1
Fig 1
Example of one of the obtained images and how the numerical evaluation was performed. Image corresponds to “cine normal” acquisition mode at the II system, FOV 23 cm, PMMA thickness 16 cm. ROI 1 used for the “signal” and ROI 2 for the background; ROIs 3 to 4 used to evaluate HCSR parameter.
Fig 2
Fig 2
SNR for all the operation modes and for 16 and 28 cm PMMA thickness. II system, FOV 23 cm, and matrix sizes of 512 and 1,024.
Fig 3
Fig 3
SNR for cine mode and for 4 to 16 cm PMMA thickness. FD system, FOV 25 cm, and matrix sizes of 512 and 1,024.
Fig 4
Fig 4
HCSR. Cine acquisition in “normal dose” mode and 16 cm PMMA thickness. II system, FOV 23 cm. Visual HCSR limit 11 groups (1.6 lp/mm) on the left and 13 (2.0 lp/mm) on the right.
Fig 5
Fig 5
HCSR. Cine acquisition in the “normal dose” mode and 28 cm PMMA thickness. II system, FOV 23 cm. Visual HCSR limit ten groups (1.4 lp/mm) on the left and 12 (1.8 lp/mm) on the right.
Fig 6
Fig 6
HCSR. Cine acquisition (single mode) and 16 cm PMMA. FD system, FOV 25 cm. Visual HCSR limit 11 groups (1.6 lp/mm) on the left and 13 (2.0 lp/mm) on the right.
Fig 7
Fig 7
HCSR. Image corresponds to cine “normal mode”, FOV 23 cm, PMMA thickness 16 cm. Example for two different ROIs sizes and different positions.
Fig 8
Fig 8
HCSR parameter for all the operation modes; 16 and 28 cm PMMA. II system, FOV 23 cm.
Fig 9
Fig 9
HCSR parameter for cine mode; 4 to 16 cm of PMMA. FD system and FOV 25 cm.
See this image and copyright information in PMC

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