Literature DB >> 21502391

Optimizing analysis, visualization, and navigation of large image data sets: one 5000-section CT scan can ruin your whole day.

Katherine P Andriole1, Jeremy M Wolfe, Ramin Khorasani, S Ted Treves, David J Getty, Francine L Jacobson, Michael L Steigner, John J Pan, Arkadiusz Sitek, Steven E Seltzer.   

Abstract

UNLABELLED: The technology revolution in image acquisition, instrumentation, and methods has resulted in vast data sets that far outstrip the human observers' ability to view, digest, and interpret modern medical images by using traditional methods. This may require a paradigm shift in the radiologic interpretation process. As human observers, radiologists must search for, detect, and interpret targets. Potential interventions should be based on an understanding of human perceptual and attentional abilities and limitations. New technologies and tools already in use in other fields can be adapted to the health care environment to improve medical image analysis, visualization, and navigation through large data sets. This historical psychophysical and technical review touches on a broad range of disciplines but focuses mainly on the analysis, visualization, and navigation of image data performed during the interpretive process. Advanced postprocessing, including three-dimensional image display, multimodality image fusion, quantitative measures, and incorporation of innovative human-machine interfaces, will likely be the future. Successful new paradigms will integrate image and nonimage data, incorporate workflow considerations, and be informed by evidence-based practices. This overview is meant to heighten the awareness of the complexities and limitations of how radiologists interact with images, particularly the large image sets generated today. Also addressed is how human-machine interface and informatics technologies could combine to transform the interpretation process in the future to achieve safer and better quality care for patients and a more efficient and effective work environment for radiologists. SUPPLEMENTAL MATERIAL: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.11091276/-/DC1. RSNA, 2011

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Year:  2011        PMID: 21502391     DOI: 10.1148/radiol.11091276

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  30 in total

1.  Image toggling saves time in mammography.

Authors:  Trafton Drew; Avi M Aizenman; Matthew B Thompson; Mark D Kovacs; Michael Trambert; Murray A Reicher; Jeremy M Wolfe
Journal:  J Med Imaging (Bellingham)       Date:  2015-10-12

2.  Imaging-based observational databases for clinical problem solving: the role of informatics.

Authors:  Alex A T Bui; William Hsu; Corey Arnold; Suzie El-Saden; Denise R Aberle; Ricky K Taira
Journal:  J Am Med Inform Assoc       Date:  2013-06-17       Impact factor: 4.497

3.  Scanners and drillers: characterizing expert visual search through volumetric images.

Authors:  Trafton Drew; Melissa Le-Hoa Vo; Alex Olwal; Francine Jacobson; Steven E Seltzer; Jeremy M Wolfe
Journal:  J Vis       Date:  2013-08-06       Impact factor: 2.240

4.  Workflow Lexicons in Healthcare: Validation of the SWIM Lexicon.

Authors:  Chris Meenan; Bradley Erickson; Nancy Knight; Jewel Fossett; Elizabeth Olsen; Prerna Mohod; Joseph Chen; Steve G Langer
Journal:  J Digit Imaging       Date:  2017-06       Impact factor: 4.056

5.  vPSNR: a visualization-aware image fidelity metric tailored for diagnostic imaging.

Authors:  Claes Lundström
Journal:  Int J Comput Assist Radiol Surg       Date:  2012-10-16       Impact factor: 2.924

Review 6.  Informatics in radiology: what can you see in a single glance and how might this guide visual search in medical images?

Authors:  Trafton Drew; Karla Evans; Melissa L-H Võ; Francine L Jacobson; Jeremy M Wolfe
Journal:  Radiographics       Date:  2012-10-25       Impact factor: 5.333

7.  [Automatic segmentation and annotation in radiology].

Authors:  P Dankerl; A Cavallaro; M Uder; M Hammon
Journal:  Radiologe       Date:  2014-03       Impact factor: 0.635

8.  Trauma in CT: The Role of Severe Injury on Satisfaction of Search Revised.

Authors:  Kevin M Schartz; Mark T Madsen; John Kim; Riko Ohashi; Kenjirou Ohashi; George Y El-Khoury; Robert T Caldwell; Edmund A Franken; Kevin S Berbaum
Journal:  J Am Coll Radiol       Date:  2016-06-18       Impact factor: 5.532

9.  Predicting visual semantic descriptive terms from radiological image data: preliminary results with liver lesions in CT.

Authors:  Adrien Depeursinge; Camille Kurtz; Christopher Beaulieu; Sandy Napel; Daniel Rubin
Journal:  IEEE Trans Med Imaging       Date:  2014-05-01       Impact factor: 10.048

10.  Multiple diagnostic task performance in CT examination of the chest.

Authors:  K M Schartz; K S Berbaum; M T Madsen; B H Thompson; B F Mullan; R T Caldwell; B Hammett; A N Ellingson; E A Franken
Journal:  Br J Radiol       Date:  2012-09-06       Impact factor: 3.039

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