Active region models for segmenting medical images

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...

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Bibliographic Details
Published inProceedings of 1st International Conference on Image Processing Vol. 2; pp. 227 - 231 vol.2
Main Authors Ivins, J., Porrill, J.
Format Conference Proceeding
LanguageEnglish
Published IEEE Comput. Soc. Press 1994
Subjects
Active contours
Artificial intelligence
Biomedical imaging
Computed tomography
Contracts
Counting circuits
Differential equations
Image reconstruction
Image segmentation
Nuclear magnetic resonance
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Summary: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.< >
ISBN:0818669527
9780818669521
DOI:10.1109/ICIP.1994.413565