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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Bochenek, A., Reicher, M.: The human anatomy. Wydawnictwo Lekarskie PZWL, Warsaw (1990)
Goslinski, J.: Pancreatic cancer—first symptoms, Oncological portal (2019)
Ito, M., Makino, N., Ueno, Y.: Glucose intolerance and the risk of pancreatic cancer. Transl. Gastrointest. Cancer 2(4), 223–229 (2013)
Summers, R.: Progress in fully automated abdominal CT interpretation. Am. J. Roentgenol. 207(1), 67–79 (2016)
Iglesias, J., Sabuncu, M.: Multi-atlas segmentation of biomedical images: a survey. Med. Image Anal. 24(1), 205–219 (2015)
Karasawa, K., Oda, M., Kitasaka, T., Misawa, K., Fujiwara, M., Chu, C., Zheng, G., Rueckert, D., Mori, K.: Multi-atlas pancreas segmentation: atlas selection based on vessel structure. Med. Image Anal. 39, 18–28 (2017)
Wolz, R., Chu, C., Misawa, K., Fujiwara, M., Mori, K., Rueckert, D.: Automated abdominal multi-organ segmentation with subject-specific atlas generation. IEEE Trans. Med. Imaging 32(9), 1723–1730 (2013)
Roth, H., Lu, L., Lay, N., Harrison, A., Farag, A., Sohn, A., Summers, R.: Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation. Med. Image Anal. 45, 94–107 (2018)
Zarychta, P.: A new approach to knee joint arthroplasty. Comput. Med. Imaging Graph. 65, 32–45 (2018)
Zarychta, P.: Patella—atlas based segmentation. In: Pietka, E., Badura, P., Kawa, J., Wieclawek, W., (eds.) Information Technologies in Medicine, Advances in Intelligent Systems and Computing, vol. 1011, pp. 314–322 (2019)
Udupa, J., Samarasekera, S.: Fuzzy connectedness and object definition: theory, algorithms, and applications. Graph. Models Image Process. 58, 246–261 (1996)
Zarychta, P.: ACL and PCL of the knee joint in the computer diagnostics. In: Napieralski A., (ed.) 21st International Conference Mixed Design of Integrated Circuits and Systems MIXDES, pp. 489–492 (2014)
Zarychta, P., Zarychta-Bargiela, A.: Anterior and posterior cruciate ligament-extraction and 3D visualization. In: Pietka E., Kawa J., (eds). Information Technologies in Biomedicine, Advances in Intelligent and Soft Computing, vol. 69. Springer, Berlin, pp. 115–122 (2010)
Zarychta P.: Automatic registration of the medical images T1- and T2-weighted MR knee images. In: Napieralski A., (ed.) International Conference Mixed Design of Integrated Circuits and Systems MIXDES, pp. 741–745 (2006)
Spinczyk, D., Zysk, A., Sperka, P., Stronczek, M., Pycinski, B., Juszczyk, J., Biesok, M., Rudzki, M., Wieclawek, W., Zarychta, P., Woloshuk, A., Zylkowski, J., Rosiak, G., Konecki, D., Mielczarek, K., Rowinski, O., Pietka, E.: Supporting diagnostics and therapy planning for percutaneous ablation of liver and abdominal tumors and preclinical evaluation. Comput. Med. Imaging Graph. 78, 101664 (2019)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Zarychta, P. (2021). Pancreas and Duodenum—Automated Organ Segmentation. In: Pietka, E., Badura, P., Kawa, J., Wieclawek, W. (eds) Information Technology in Biomedicine. Advances in Intelligent Systems and Computing, vol 1186. Springer, Cham. https://doi.org/10.1007/978-3-030-49666-1_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-49666-1_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-49665-4
Online ISBN: 978-3-030-49666-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)