Dependency of image quality on acquisition protocol and image processing in chest tomosynthesis-a visual grading study based on clinical data

Image processing setting adaptions according to image dose and radiologist preference can improve image quality in computed radiography of the equine distal limb: A cadaveric study

Image processing (IP) in digital radiography has been steadily refined to improve image quality. Adaptable settings enable users to adjust systems to their specific requirements. This prospective, analytical study aimed to investigate the influence of different IP settings and dose reductions on image quality. Included were 20 cadaveric equine limb specimens distal to the metacarpophalangeal and metatarsophalangeal joints. Images were processed with the Dynamic Visualization II system (Fujifilm) using five different IP settings including multiobjective frequency processing, flexible noise control (FNC), and virtual grid processing (VGP). Seven criteria were assessed by three veterinary radiology Diplomates and one veterinary radiology resident in a blinded study using a scoring system. Algorithm comparison was performed using an absolute visual grading analysis. The rating of bone structures was improved by VGP at full dose (P < .05; AUCVGC  = 0.45). Überschwinger artifact perception was enhanced by VGP (P < .001; AUCVGC  = 0.66), whereas image noise perception was suppressed by FNC (P < .001; AUCVGC  = 0.29). The ratings of bone structures were improved by FNC at 50% dose (P < .05; AUCVGC  = 0.44), and 25% dose (P < .001; AUCVGC  = 0.32), and clinically acceptable image quality was maintained at 50% dose (mean rating 2.16; 95.8% ratings sufficient or better). The favored IP setting varied among observers, with higher agreement at lower dose levels. These findings supported using individualized IP settings based on the radiologist's preferences and situational image requirements, rather than using default settings.

VIEWDEX 3.0-RECENT DEVELOPMENT OF A SOFTWARE APPLICATION FACILITATING ASSESSMENT OF IMAGE QUALITY AND OBSERVER PERFORMANCE

ViewDEX (Viewer for Digital Evaluation of X-ray Images) is an image viewer compatible with Digital Imaging and Communications in Medicine (DICOM) that has been especially designed to facilitate image perception and observer performance studies within medical imaging. The software was first released in 2004 and since then a continuous development has been ongoing. One of the major drawbacks of previous versions of ViewDEX has been that they have lacked functionality enabling the possibility to evaluate multiple images and/or image stacks simultaneously. This functionality is especially requested by researchers working with modalities, where an image acquisition can result in multiple image stacks (e.g. axial, coronal and sagittal reformations in computed tomography). In ViewDEX 3.0 this functionality has been added and it is now possible to perform image evaluations of multiple images and/or image stacks simultaneously, by using multiple monitors and/or multiple image canvases in monitors. Additionally, some of the previously available functionality has been updated and improved. This paper describes the recent developments of ViewDEX 3.0.

EVALUATION OF VGC ANALYZER BY COMPARISON WITH GOLD STANDARD ROC SOFTWARE AND ANALYSIS OF SIMULATED VISUAL GRADING DATA

The purpose of the present work was to evaluate the use of resampling statistical methods for analysis of visual grading data-implemented in the software VGC Analyzer-by comparing the reanalyzed results from previously performed visual grading studies with the results calculated by gold standard receiver operating characteristic (ROC) methodology, Obuchowski-Rockette (OR)-Dorfman-Berbaum-Metz (DBM) multiple-readers and multiple-case (MRMC) and by analysis of simulated visual grading data where the true distribution was presumed to be known. The reanalysis was performed on two multiple-reader studies with non-paired data and paired data, respectively. The simulation study was performed by simulating a large number of visual grading characteristics (VGC) studies and by analyzing the statistical distribution of null hypothesis (H0) rejection rate. The comparison with OR-DBM MRMC showed good agreement when analyzing non-paired data for both fixed-reader and random-reader settings for the calculated area under the curve values and the confidence intervals (CIs). For paired data analysis, VGC Analyzer showed significantly lower CIs compared with the ROC software. This effect was also illustrated by the simulation study, where the VGC Analyzer, in general, showed good accuracy for simulated studies with stable statistical basis. For simulated studies with unstable statistics, the accuracy in the H0 rejection rate decreased. The present study has shown that resampling methodology can be used to accurately perform the statistical analysis of a VGC study, although the resampling technique used makes the method sensitive to small data sets.