
Proceedings Paper
Comparing the Microsoft Kinect to a traditional mouse for adjusting the viewed tissue densities of three-dimensional anatomical structuresFormat | Member Price | Non-Member Price |
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Paper Abstract
Advancements in medical image visualization in recent years have enabled three-dimensional (3D) medical images to be volume-rendered from magnetic resonance imaging (MRI) and computed tomography (CT) scans. Medical data is crucial for patient diagnosis and medical education, and analyzing these three-dimensional models rather than two-dimensional (2D) slices would enable more efficient analysis by surgeons and physicians, especially non-radiologists. An interaction device that is intuitive, robust, and easily learned is necessary to integrate 3D modeling software into the medical community. The keyboard and mouse configuration does not readily manipulate 3D models because these traditional interface devices function within two degrees of freedom, not the six degrees of freedom presented in three dimensions. Using a familiar, commercial-off-the-shelf (COTS) device for interaction would minimize training time and enable maximum usability with 3D medical images. Multiple techniques are available to manipulate 3D medical images and provide doctors more innovative ways of visualizing patient data. One such example is windowing. Windowing is used to adjust the viewed tissue density of digital medical data. A software platform available at the Virtual Reality Applications Center (VRAC), named Isis, was used to visualize and interact with the 3D representations of medical data. In this paper, we present the methodology and results of a user study that examined the usability of windowing 3D medical imaging using a Kinect™ device compared to a traditional mouse.
Paper Details
Date Published: 28 March 2013
PDF: 10 pages
Proc. SPIE 8673, Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment, 86731M (28 March 2013); doi: 10.1117/12.2006994
Published in SPIE Proceedings Vol. 8673:
Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment
Craig K. Abbey; Claudia R. Mello-Thoms, Editor(s)
PDF: 10 pages
Proc. SPIE 8673, Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment, 86731M (28 March 2013); doi: 10.1117/12.2006994
Show Author Affiliations
Bethany Juhnke, Iowa State Univ. (United States)
Monica Berron, Univ. of Maryland, Baltimore County (United States)
Adriana Philip, The Pennsylvania State Univ. (United States)
Monica Berron, Univ. of Maryland, Baltimore County (United States)
Adriana Philip, The Pennsylvania State Univ. (United States)
Jordan Williams, Univ. of Maryland, Baltimore County (United States)
Joseph Holub, Iowa State Univ. (United States)
Eliot Winer, Iowa State Univ. (United States)
Joseph Holub, Iowa State Univ. (United States)
Eliot Winer, Iowa State Univ. (United States)
Published in SPIE Proceedings Vol. 8673:
Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment
Craig K. Abbey; Claudia R. Mello-Thoms, Editor(s)
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