Paper
7 March 2013 Real-time volume rendering of digital medical images on an iOS device
Christian Noon, Joseph Holub, Eliot Winer
Author Affiliations +
Proceedings Volume 8667, Multimedia Content and Mobile Devices; 86670U (2013) https://doi.org/10.1117/12.2005335
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States
Abstract
Performing high quality 3D visualizations on mobile devices, while tantalizingly close in many areas, is still a quite difficult task. This is especially true for 3D volume rendering of digital medical images. Allowing this would empower medical personnel a powerful tool to diagnose and treat patients and train the next generation of physicians. This research focuses on performing real time volume rendering of digital medical images on iOS devices using custom developed GPU shaders for orthogonal texture slicing. An interactive volume renderer was designed and developed with several new features including dynamic modification of render resolutions, an incremental render loop, a shader-based clipping algorithm to support OpenGL ES 2.0, and an internal backface culling algorithm for properly sorting rendered geometry with alpha blending. The application was developed using several application programming interfaces (APIs) such as OpenSceneGraph (OSG) as the primary graphics renderer coupled with iOS Cocoa Touch for user interaction, and DCMTK for DICOM I/O. The developed application rendered volume datasets over 450 slices up to 50-60 frames per second, depending on the specific model of the iOS device. All rendering is done locally on the device so no Internet connection is required.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Christian Noon, Joseph Holub, and Eliot Winer "Real-time volume rendering of digital medical images on an iOS device", Proc. SPIE 8667, Multimedia Content and Mobile Devices, 86670U (7 March 2013); https://doi.org/10.1117/12.2005335
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CITATIONS
Cited by 6 scholarly publications.
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KEYWORDS
Volume rendering

Information operations

Cameras

OpenGL

Medical imaging

Mobile devices

Switches

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