Visual detection efficiency in ultrasonic imaging: A framework for objective assessment of image quality

1994 ◽  
Vol 95 (4) ◽  
pp. 2081-2090 ◽  
Author(s):  
Michael F. Insana ◽  
Timothy J. Hall
1998 ◽  
Vol 71 (841) ◽  
pp. 48-58 ◽  
Author(s):  
A D Castellano Smith ◽  
I A Castellano Smith ◽  
D R Dance

2007 ◽  
pp. 101-114
Author(s):  
Matthew A. Kupinski ◽  
Eric Clarkson

2020 ◽  
Vol 149 ◽  
pp. 02013
Author(s):  
Evgenii A. Maltsev ◽  
Yurii A. Maglinets ◽  
Ruslan V. Brezhnev

The method of the objective evaluation of the satellite images based on the calculation of the geometrical concentration using triangulation Delaunay is proposed. Such assessment allows to estimate the degree of the image distortion and can be used for indexing and filtration data in the satellite images catalogues.


2018 ◽  
Vol 25 (4) ◽  
pp. 1093-1105
Author(s):  
Yanping Wang ◽  
Gang Li ◽  
Jie Zhang ◽  
Qiru Yi ◽  
Yue Zhao ◽  
...  

Lens-coupled indirect X-ray imaging detectors have the advantage of high resolution and the disadvantage of low detection efficiency. Using thicker single-crystalline films (SCFs) can improve the detection efficiency. However, the image quality will become worse due to the degradation of the point spread function (PSF) and modulation transfer function (MTF). This disadvantage can be improved by deconvolution with the PSF, which is unknown. In this article, a method was established to acquire the PSF based on a simulation of the imaging process for a lens-coupled indirect X-ray imaging detector. Because the structural parameters of commercial lenses cannot usually be obtained, the PSFs were calculated from lens performance parameters. PSFs were calculated using the conditions of 12 keV X-ray energy, 10× and 40× magnification objectives and 4.6 µm- and 20 µm-thick GGG:Tb scintillators. These were then used to deconvolve images of an Xradia resolution test pattern taken under the same conditions. The results show that after deconvolution the MTF had been clearly improved for both the 4.6 µm- and 20 µm-thick SCFs, indicating that the image has better quality than before deconvolution. Furthermore, a PSF deconvolution was performed on mouse brain tissue projection images, and the original and deconvolution projection images were used to perform computed-tomography reconstruction; the result proved that the method was effective for improving the image quality of low-contrast samples. Therefore, this method shows promise in allowing the use of thick SCFs to improve the detection efficiency while maintaining good image quality.


2018 ◽  
Vol 13 (1) ◽  
pp. 155-162 ◽  
Author(s):  
Peng Zhou ◽  
Chunling Zhang ◽  
Zhen Gao ◽  
Wangshu Cai ◽  
Deyue Yan ◽  
...  

AbstractObjectiveTo evaluate the practical effectiveness of smart metal artifact reduction (SMAR) in reducing artifacts caused by metallic implants.MethodsPatients with metal implants underwent computed tomography (CT) examinations on high definition CT scanner, and the data were reconstructed with adaptive statistical iterative reconstruction (ASiR) with value weighted to 40% and smart metal artifact reduction (SMAR) technology. The comparison was assessed by both subjective and objective assessment between the two groups of images. In terms of subjective assessment, three radiologists evaluated image quality and assigned a score for visualization of anatomic structures in the critical areas of interest. Objectively, the absolute CT value of the difference (ΔCT) and artifacts index (AI) were adopted in this study for the quantitative assessment of metal artifacts.ResultsIn subjective image quality assessment, three radiologists scored SMAR images higher than 40% ASiR images (P<0.01) and the result suggested that visualization of critical anatomic structures around the region of the metal object was significantly improved by using SMAR compared with 40% ASiR. The ΔCT and AI for quantitative assessment of metal artifacts showed that SMAR appeared to be superior for reducing metal artifacts (P<0.05) and indicated that this technical approach was more effective in improving the quality of CT images.ConclusionA variety of hardware (dental filling, embolization coil, instrumented spine, hip implant, knee implant) are processed with the SMAR algorithm to demonstrate good recovery of soft tissue around the metal. This artifact reduction allows for the clearer visualization of structures hidden underneath.


1994 ◽  
Vol 7 (2) ◽  
pp. 77-78 ◽  
Author(s):  
Walter F. Good ◽  
David Gur ◽  
John H. Feist ◽  
F. Leland Thaete ◽  
Carl R. Fuhrman ◽  
...  

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