@inbook{2b9e870e002d4918b321ecad55090f0e,
title = "Pancreas and duodenum—automated organ segmentation",
abstract = "The goal of this preliminary research is to present an automated segmentation of abdominal organs: pancreas and duodenum. The paper shows the automatic extraction of pancreas and duodenum in clinical abdominal computed tomography (CT) scans. The proposed method allows building a feature vector that automates and streamlines the fuzzy connectedness (FC) method. All described steps of the presented methodology have been implemented in MATLAB and tested on clinical abdominal CT scans. The atlas based segmentation combined with the FC method gave Dice index results at the following level: 70.18–84.82\% for pancreas and 68.90–88.06\% for duodenum.",
keywords = "Atlas based segmentation, Duodenum, Fuzzy connectedness, Pancreas",
author = "Piotr Zarychta",
note = "Publisher Copyright: {\textcopyright} The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.",
year = "2021",
doi = "10.1007/978-3-030-49666-1\_8",
language = "English",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer",
pages = "95--105",
booktitle = "Advances in Intelligent Systems and Computing",
address = "Germany",
}