NDLI: Active region models for segmenting medical images

Content Provider	IEEE Xplore Digital Library
Author	Ivins, J. Porrill, J.
Copyright Year	1994
Description	Author affiliation: AI Vision Res. Unit, Sheffield Univ., UK (Ivins, J.; Porrill, J.)
Abstract	Describes a new region-growing method for segmenting medical images. The method uses a closed snake driven by a pressure force that is a function of the statistical characteristics of image data. This statistical snake expands until it encounters pixels that lie outside user-defined limits relative to a seed region; when these limits are violated the pressure force is reversed to make the model contract. Tension and stiffness forces keep the boundary of the region model smooth, and a repulsion force prevents self-intersection. Boundary elements can be added and removed in response to complexity changes, and the tension, stiffness and pressure parameters can be adjusted to preserve the energy balance of the changing model. Statistical snakes have been used to reconstruct various anatomical features from NMR and CT volumes.
Starting Page	227
Ending Page	231
File Size	399609
Page Count	5
File Format	PDF
ISBN	0818669527
DOI	10.1109/ICIP.1994.413565
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1994-11-13
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Biomedical imaging Image reconstruction Nuclear magnetic resonance Contracts Differential equations Artificial intelligence Counting circuits Computed tomography Active contours
Content Type	Text
Resource Type	Article

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