The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.05 - May (2003 vol.25)
pp: 550-563
ABSTRACT
<p><b>Abstract</b>—We present a discrete contour model for the segmentation of image data with any dimension of image domain and value range. The model consists of a representation using simplex meshes and a mechanical formulation of influences that drive an iterative segmentation. The object's representation as well as the influences are valid for any dimension of the image domain. The image influences introduced here, can combine information from independent channels of higher-dimensional value ranges. Additionally, the topology of the model automatically adapts to objects contained in images. Noncontextual tests have validated the ability of the model to reproducibly delineate synthetic objects. In particular, images with a signal to noise ratio of SNR <tmath>\leq 0.5</tmath> are delineated within two pixels of their ground truth contour. Contextual validations have shown the applicability of the model for medical image analysis in image domains of two, three, and four dimensions in single as well as multichannel value ranges.</p>
INDEX TERMS
Discrete contour model, segmentation, volumetric, spatio-temporal, multichannel, topology-adaptive, tracking.
CITATION
Thomas M. Lehmann, Klaus Spitzer, "A General Discrete Contour Model in Two, Three, and Four Dimensions for Topology-Adaptive Multichannel Segmentation", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.25, no. 5, pp. 550-563, May 2003, doi:10.1109/TPAMI.2003.1195990
31 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool