Literature DB >> 16854962

Visual grading characteristics (VGC) analysis: a non-parametric rank-invariant statistical method for image quality evaluation.

M Båth1, L G Månsson.   

Abstract

Visual grading of the reproduction of important anatomical structures is often used to determine clinical image quality in radiography. However, many visual grading methods incorrectly use statistical methods that require data belonging to an interval scale. The rating data from the observers in a visual grading study with multiple ratings is ordinal, meaning that non-parametric rank-invariant statistical methods are required. This paper describes such a method for determining the difference in image quality between two modalities called visual grading characteristics (VGC) analysis. In a VGC study, the task of the observer is to rate his confidence about the fulfilment of image quality criteria. The rating data for the two modalities are then analysed in a manner similar to that used in receiver operating characteristics (ROC) analysis. The resulting measure of image quality is the VGC curve, which--for all possible thresholds of the observer for a fulfilled criterion--describes the relationship between the proportions of fulfilled image criteria for the two compared modalities. The area under the VGC curve is proposed as a single measure of the difference in image quality between two compared modalities. It is also described how VGC analysis can be applied to data from an absolute visual grading analysis study.

Mesh:

Year:  2006        PMID: 16854962     DOI: 10.1259/bjr/35012658

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  53 in total

1.  Strict X-ray beam collimation for facial bones examination can increase lens exposure.

Authors:  R Powys; J Robinson; P L Kench; J Ryan; P C Brennan
Journal:  Br J Radiol       Date:  2012-02-28       Impact factor: 3.039

2.  Quantifying the potential for dose reduction with visual grading regression.

Authors:  O Smedby; M Fredrikson; J De Geer; L Borgen; M Sandborg
Journal:  Br J Radiol       Date:  2012-06-20       Impact factor: 3.039

Review 3.  Diagnostic imaging--evaluating image quality using visual grading characteristic (VGC) analysis.

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4.  The impact of pediatric-specific dose modulation curves on radiation dose and image quality in head computed tomography.

Authors:  Joana Santos; Shane Foley; Graciano Paulo; Mark F McEntee; Louise Rainford
Journal:  Pediatr Radiol       Date:  2015-08-05

5.  New developed DR detector performs radiographs of hand, pelvic and premature chest anatomies at a lower radiation dose and/or a higher image quality.

Authors:  Helle Precht; Anders Tingberg; Dag Waaler; Claus Bjørn Outzen
Journal:  J Digit Imaging       Date:  2014-02       Impact factor: 4.056

6.  Visual grading of 2D and 3D functional MRI compared with image-based descriptive measures.

Authors:  Mattias Ragnehed; Olof Dahlqvist Leinhard; Johan Pihlsgård; Staffan Wirell; Hannibal Sökjer; Patrik Fägerstam; Bo Jiang; Orjan Smedby; Maria Engström; Peter Lundberg
Journal:  Eur Radiol       Date:  2009-09-02       Impact factor: 5.315

7.  Visual grading regression: analysing data from visual grading experiments with regression models.

Authors:  O Smedby; M Fredrikson
Journal:  Br J Radiol       Date:  2010-03-11       Impact factor: 3.039

8.  Motion compensation in extremity cone-beam computed tomography.

Authors:  Alejandro Sisniega; Gaurav K Thawait; Delaram Shakoor; Jeffrey H Siewerdsen; Shadpour Demehri; Wojciech Zbijewski
Journal:  Skeletal Radiol       Date:  2019-06-06       Impact factor: 2.199

9.  Evaluation of a new system for chest tomosynthesis: aspects of image quality of different protocols determined using an anthropomorphic phantom.

Authors:  M Jadidi; A Sundin; P Aspelin; M Båth; S Nyrén
Journal:  Br J Radiol       Date:  2015-06-29       Impact factor: 3.039

10.  Agreement between objective and subjective assessment of image quality in ultrasound abdominal aortic aneurism screening.

Authors:  S Wolstenhulme; A G Davies; C Keeble; S Moore; J A Evans
Journal:  Br J Radiol       Date:  2014-12-11       Impact factor: 3.039

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