@inproceedings{5470e91ad19048afa16cc45b006f5f0f,
title = "Segmentation of cervical images by inter-subject registration with a statistical organ model",
abstract = "For radiation therapy of cervical cancer, segmentation of the cervix and the surrounding organs are needed. The aim is to develop a fully automatic method for the segmentation of all relevant organs. Our approach is an atlas-based segmentation, with a registration scheme that is aided by statistical knowledge of the deformations that are to be expected. A statistical model that acts on the boundary of an organ is included as a soft constraint in a free-form registration framework. As a first evaluation of our approach, we apply it to the segmentation of the bladder. Statistical models for the bladder were trained on a set of manual delineations. Experiments on a leave-one-patient-out basis were performed, with the quality defined as the Dice similarity to the manual segmentations. Compared to a registration without the use of statistical knowledge, the segmentations are slightly, but significantly improved. {\textcopyright} 2012 Springer-Verlag.",
author = "F.F. Berendsen and {Heide, van der}, U.A. and T.R. Langerak and A.N.T.J. Kotte and J.P.W. Pluim",
year = "2012",
doi = "10.1007/978-3-642-28557-8_30",
language = "English",
isbn = "978-3-642-28556-1",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "240--247",
editor = "H. Yoshida and G. Sakas and M.G. Linguraru",
booktitle = "Abdominal imaging : computational and clinical applications : Third International Workshop, Held in Conjunction with MICCAI 2011, Toronto, ON, Canada, September 18, 2011, revised selected papers",
address = "Germany",
note = "3rd International Workshop on Computational and Clinical Applications in Abdominal Imaging, September 18, 2011, Toronto, Canada ; Conference date: 18-09-2011",
}
