@inproceedings{a2afd325aca1443d9d0fca10a82eb436,
title = "Patella {\textendash} Atlas Based Segmentation",
abstract = "The main aim of this research is to present an automated image segmentation methodology being used in the field of medicine. The paper shows the automatic extraction of patella in the knee joint based on atlas segmentation. This method allows to build a feature vector that automates and streamlines known segmentation methods (e.g. fuzzy c-means (FCM), fuzzy connectedness (FC)). The described methodology has been implemented in MATLAB and tested on clinical computed tomography (CT) slices of the knee joint in transverse plane.",
keywords = "Atlas based segmentation, FC, FCM, Knee joint, Patella",
author = "Piotr Zarychta",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 7th International Conference on Information Technology in Biomedicine, ITIB 2019 ; Conference date: 18-06-2019 Through 20-06-2019",
year = "2019",
doi = "10.1007/978-3-030-23762-2\_28",
language = "English",
isbn = "9783030237615",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "314--322",
editor = "Ewa Pietka and Pawel Badura and Jacek Kawa and Wojciech Wieclawek",
booktitle = "Information Technology in Biomedicine, 2019",
address = "Germany",
}