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Alternative user interface devices for improved navigation of CT datasets
Örebro University, School of Health and Medical Sciences.
Örebro University, School of Health and Medical Sciences.
Örebro University, School of Health and Medical Sciences.ORCID iD: 0000-0003-3253-8967
2011 (English)In: Journal of digital imaging, ISSN 0897-1889, E-ISSN 1618-727X, Vol. 24, no 1, 126-134 p.Article in journal (Refereed) Published
Abstract [en]

The workflow in radiology departments has changed dramatically with the transition to digital PACS, especially with the shift from tile mode to stack mode display of volumetric images. With the increasing number of images in routinely captured datasets, the standard user interface devices (UIDs) become inadequate. One basic approach to improve the navigation of the stack mode datasets is to take advantage of alternative UIDs developed for other domains, such as the computer game industry. We evaluated three UIDs both in clinical practice and in a task-based experiment. After using the devices in the daily image interpretation work, the readers reported that both of the tested alternative UIDs were better in terms of ergonomics compared to the standard mouse and that both alternatives were more efficient when reviewing large CT datasets. In the task-based experiment, one of the tested devices was faster than the standard mouse, while the other alternative was not significantly faster. One of the tested alternative devices showed a larger number of traversed images during the task. The results indicate that alternative user interface devices can improve the navigation of stack mode datasets and that radiologists should consider the potential benefits of alternatives to the standard mouse.

Place, publisher, year, edition, pages
Springer, 2011. Vol. 24, no 1, 126-134 p.
Keyword [en]
navigation, user interface, PACS, computed tomography
National Category
Medical and Health Sciences Radiology, Nuclear Medicine and Medical Imaging
Research subject
Medicine
Identifiers
URN: urn:nbn:se:oru:diva-12074DOI: 10.1007/s10278-009-9252-2ISI: 000286469600014PubMedID: 19949832Scopus ID: 2-s2.0-79751523933OAI: oai:DiVA.org:oru-12074DiVA: diva2:355154
Available from: 2010-10-05 Created: 2010-10-05 Last updated: 2017-12-12Bibliographically approved
In thesis
1. The stack mode review of volumetric datasets: applications for urinary stone disease
Open this publication in new window or tab >>The stack mode review of volumetric datasets: applications for urinary stone disease
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

During the last decades the acquisition and visualization of radiological images have rapidly evolved. The increasing amounts of volumetric image data particularly from modern CT systems necessitate a constant evolution of the radiological visualization techniques.

The dominating display mode for volumetric images has been the stack mode display since its introduction in computerized image review. In the increasing amounts of image data, the stack mode display needs to be analyzed so that the information content in the high resolution datasets can be transformed into clinically relevant information for the management of the individual patient. In the present thesis some aspects of the stack mode display were analyzed using for the most part the size estimation of urinary stones in unenhanced CT as a model.

The estimated size has an important correlation to the prognosis for spontaneous passage of an obstructing ureteral stone. In the present thesis the reader variations in the size estimation of urinary stones were quantified, using different visualization parameters and after an attempt to reduce the variations with a training session for the readers. The influence on the estimated stone size of CT image post processing parameters was quantified. A segmentation algorithm was developed and demonstrated to reduce the reader variability through reader independent computer aid. One limitation of the stack mode display concerns three-dimensional shapes, which was modeled by a comparison between the estimated length and width of urinary stones in two- and three-dimensional segmentation. The increasing number of image slices in the acquisitions introduces a need for efficient navigation of the image volumes. In the present thesis the navigation of CT datasets using different user interface devices was evaluated.

The rapid evolution of the MRI and CT systems necessitates a constant refinement and evaluation of the cornerstone for radiological volumetric reviewing – the stack mode display of volumetric datasets.

Place, publisher, year, edition, pages
Örebro: Örebro universitet, 2013. 61 p.
Series
Örebro Studies in Medicine, ISSN 1652-4063 ; 91
Keyword
stack mode display, image visualization, image perception, computed tomography, urinary stones, urolithiasis, PACS
National Category
Radiology, Nuclear Medicine and Medical Imaging
Research subject
Medicine
Identifiers
urn:nbn:se:oru:diva-30324 (URN)978-91-7668-948-6 (ISBN)
Public defence
2013-10-04, Bohmanssonsalen, Universitetssjukhuset i Örebro, Örebro, 09:00 (Swedish)
Opponent
Supervisors
Available from: 2013-08-26 Created: 2013-08-26 Last updated: 2017-10-17Bibliographically approved

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Lidén, MatsAndersson, TorbjörnGeijer, Håkan

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