@inproceedings{9ea50fd313cd46b49e2eae002f09964e,
title = "Adaptive unsupervised contextual Bayesian segmentation: application on images of blood vessel",
abstract = "Mixture estimation has been widely applied to unsupervised contextual Bayesian segmentation. We present at first the algorithms which estimate distribution mixtures prior to contextual segmentation, such as estimation-maximization (EM), iterative conditional estimation (ICE), and their adaptive versions valid for nonstationary class fields. Upon removing the stationarity hypothesis, contextual segmentation can give much better results in certain cases. Results obtained attest to the suitability of adaptive versions of EM, ICE valid in the case of nonstationary random class fields. Then we present our experiences on the application of the unsupervised contextual Bayesian segmentation to images of blood vessel.",
author = "Anrong Peng and Wojciech Pieczynski",
year = "1994",
month = dec,
day = "1",
language = "English",
isbn = "0819416231",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "Publ by Society of Photo-Optical Instrumentation Engineers",
pages = "357--366",
editor = "Bookstein, \{Fred L.\} and Duncan, \{James S.\} and Nicholas Lange and Wilson, \{David C.\}",
booktitle = "Proceedings of SPIE - The International Society for Optical Engineering",
note = "Mathematical Methods in Medical Imaging III ; Conference date: 25-07-1994 Through 26-07-1994",
}