Literature DB >> 18383686

Anniversary paper: evaluation of medical imaging systems.

Elizabeth A Krupinski1, Yulei Jiang.   

Abstract

Medical imaging used to be primarily within the domain of radiology, but with the advent of virtual pathology slides and telemedicine, imaging technology is expanding in the healthcare enterprise. As new imaging technologies are developed, they must be evaluated to assess the impact and benefit on patient care. The authors review the hierarchical model of the efficacy of diagnostic imaging systems by Fryback and Thornbury [Med. Decis. Making 11, 88-94 (1991)] as a guiding principle for system evaluation. Evaluation of medical imaging systems encompasses everything from the hardware and software used to acquire, store, and transmit images to the presentation of images to the interpreting clinician. Evaluation of medical imaging systems can take many forms, from the purely technical (e.g., patient dose measurement) to the increasingly complex (e.g., determining whether a new imaging method saves lives and benefits society). Evaluation methodologies cover a broad range, from receiver operating characteristic (ROC) techniques that measure diagnostic accuracy to timing studies that measure image-interpretation workflow efficiency. The authors review briefly the history of the development of evaluation methodologies and review ROC methodology as well as other types of evaluation methods. They discuss unique challenges in system evaluation that face the imaging community today and opportunities for future advances.

Entities:  

Mesh:

Year:  2008        PMID: 18383686     DOI: 10.1118/1.2830376

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  11 in total

Review 1.  Current perspectives in medical image perception.

Authors:  Elizabeth A Krupinski
Journal:  Atten Percept Psychophys       Date:  2010-07       Impact factor: 2.199

2.  A Brief Survey on No-Reference Image Quality Assessment Methods for Magnetic Resonance Images.

Authors:  Igor Stępień; Mariusz Oszust
Journal:  J Imaging       Date:  2022-06-04

3.  Performance assessments of diagnostic systems under the FROC paradigm: experimental, analytical, and results interpretation issues.

Authors:  David Gur; Howard E Rockette
Journal:  Acad Radiol       Date:  2008-10       Impact factor: 3.173

4.  Performance of diagnostic mammography differs in the United States and Denmark.

Authors:  Allan Jensen; Berta M Geller; Charlotte C Gard; Diana L Miglioretti; Bonnie Yankaskas; Patricia A Carney; Robert D Rosenberg; Ilse Vejborg; Elsebeth Lynge
Journal:  Int J Cancer       Date:  2010-10-15       Impact factor: 7.396

5.  Performance evaluation of three computed radiography systems using methods recommended in American Association of Physicists in Medicine Report 93.

Authors:  Wilbroad Muhogora; Renato Padovani; Faustino Bonutti; Peter Msaki; R Kazema
Journal:  J Med Phys       Date:  2011-07

6.  Exploration of analysis methods for diagnostic imaging tests: problems with ROC AUC and confidence scores in CT colonography.

Authors:  Susan Mallett; Steve Halligan; Gary S Collins; Doug G Altman
Journal:  PLoS One       Date:  2014-10-29       Impact factor: 3.240

Review 7.  The Holistic Processing Account of Visual Expertise in Medical Image Perception: A Review.

Authors:  Heather Sheridan; Eyal M Reingold
Journal:  Front Psychol       Date:  2017-09-28

8.  Real-time three-dimensional MRI for the assessment of dynamic carpal instability.

Authors:  Calvin B Shaw; Brent H Foster; Marissa Borgese; Robert D Boutin; Cyrus Bateni; Pattira Boonsri; Christopher O Bayne; Robert M Szabo; Krishna S Nayak; Abhijit J Chaudhari
Journal:  PLoS One       Date:  2019-09-19       Impact factor: 3.240

9.  Pigeons (Columba livia) as Trainable Observers of Pathology and Radiology Breast Cancer Images.

Authors:  Richard M Levenson; Elizabeth A Krupinski; Victor M Navarro; Edward A Wasserman
Journal:  PLoS One       Date:  2015-11-18       Impact factor: 3.240

10.  Influence of Acquisition Time on MR Image Quality Estimated with Nonparametric Measures Based on Texture Features.

Authors:  Rafał Obuchowicz; Adam Piórkowski; Andrzej Urbanik; Michał Strzelecki
Journal:  Biomed Res Int       Date:  2019-11-20       Impact factor: 3.411

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