NDLI: Projected electronic dissection-classification and shaded projection for 3D visualization of MR images of the brain

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Projected electronic dissection-classification and shaded projection for 3D visualization of MR images of the brain

Content Provider	IEEE Xplore Digital Library
Author	Zhang, G. Liu, X. Fox, M.D.
Copyright Year	1989
Description	Author affiliation: Connecticut Univ., Storrs, CT, USA (Zhang, G.; Liu, X.; Fox, M.D.)
Abstract	Projected electronic dissection (PED) creates the effect of actually dissecting a tissue structure under examination by operating on a 3-D digitized data set. Advanced computer techniques have made it possible to range through a 3-D MRI (magnetic resonance image) data set in real time. In actual dissection, however, if a portion of a volume is sliced off, is it possible to see both the remaining external surface and any internal surfaces revealed by the removal of superficial layers. PED refers to a technique that displays not only tissue paraenchyma at the level of cut, but also these internal and external surfaces, which can be important both for orientation and diagnosis. Preliminary PED results were obtained on MRI volumetric data set of proton densities of the brain. The initial results suggest that the partial shaded projection technique described offers the prospect of providing a natural way to display and analyze experimental data from the brain and other organ systems with applications in medical diagnosis, the study of anatomy and the planning of surgery.<>
Starting Page	123
Ending Page	124
File Size	255102
Page Count	2
File Format	PDF
DOI	10.1109/NEBC.1989.36731
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1989-03-27
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Magnetic resonance imaging Computed tomography Protons Medical diagnosis Surface reconstruction Data visualization Image generation Three dimensional displays Laboratories Data engineering
Content Type	Text
Resource Type	Article

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