NDLI: Performance analysis on three dimensional surface reconstruction of head magnetic resonance images

Content Provider	IEEE Xplore Digital Library
Author	Preetha, R. Suresh, G.R.
Copyright Year	2012
Description	Author affiliation: (Anna University), Easwari Engineering College, Chennai, India (Preetha, R.) \|\| Easwari Engineering College, Chennai, India (Suresh, G.R.)
Abstract	In MRI images, the boundary of an encephalic tissue is highly curved and irregular. Three dimensional reconstruction of such encephalic tissue is complicated. The surface reconstruction is the sub-field of Medical imaging which provides an effective way to investigate and determine brain related diseases in an efficient and effective manner. The basic purpose of 3-D surface reconstruction is to analyze the brain images precisely in order to effectively diagnose and examine the diseases for surgical planning and tumor localization. Reconstruction of tumor images is the goal in dealing with these images. In this paper, a brief overview is given on the advantages and disadvantages of existing surface reconstruction methods in clinical applications. The traditional cube based algorithms extracts the surface by forming imaginary cube and then determines the polygons needed to represent the part of the isosurface that passes through this cube. But, it requires post processing and needs more Computational time for reconstruction. Also they cannot provide the proof of correctness. The vector machine based algorithms like Immune Sphere Shaped Support Vector Machine (ISSSVM) transforms the highly irregular object into the high dimensional feature space and construct the hyper-sphere as compact as possible which encloses almost all the target object. This paper concludes that ISSSVM can outperform the cube based algorithm by reconstructing the irregular boundaries of the encephalic tissue efficiently without post processing. It can also provide its proof of correctness with greater accuracy.
Starting Page	351
Ending Page	356
File Size	400561
Page Count	6
File Format	PDF
ISBN	9781467351171
ISSN	21647143
e-ISBN	9781467351195
DOI	10.1109/ISDA.2012.6416563
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-11-27
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Algorithm design and analysis Three dimensional surface reconstruction Surface reconstruction Support vector machine (SVM) Accuracy Encephalic tissue Magnetic Resonance Image (MRI) Kernel Image reconstruction Isosurfaces
Content Type	Text
Resource Type	Article

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