@inbook{5dd87099b8cc43268004ed17a74f7aa2,
title = "Fuzzy C-means techniques for medical image segmentation",
abstract = "Segmentation is an important step in many medical imaging applications and a variety of image segmentation techniques exist. One group of segmentation algorithms is based on clustering concepts. In this chapter we provide an overview of several fuzzy c-means based clustering approaches and their application to medical imaging. In particular we evaluate the conventional hard c-means and fuzzy c-means (FCM) approches as well as three computationally more efficient derivatives of fuzzy c-means: Fast FCM with random sampling, fast generalised FCM, and a new anisotropic mean shift based FCM.",
author = "Huiyu Zhou and Gerald Schaefer and Chunmei Shi",
year = "2009",
month = jan,
doi = "10.1007/978-3-540-89968-6_13",
language = "English",
isbn = "978-3-540-89967-9",
series = "Studies in Fuzziness and Soft Computing",
publisher = "Springer",
pages = "257--271",
editor = "Yaochu Jin and Lipo Wang",
booktitle = "Fuzzy systems in bioinformatics and computational biology",
address = "Germany",
}