Oyarzun Laura, Cristina ; Drechsler, Klaus ; Wesarg, Stefan (2014)
Anatomical Discovery: Finding Organs in the Neighborhood of the Liver.
XIII Mediterranean Conference on Medical and Biological Engineering and Computing.
doi: 10.1007/978-3-319-00846-2_86
Conference or Workshop Item, Bibliographie
Abstract
Image segmentation and registration algorithms are fundamental to assist medical doctors for better treatment of the patients. To this end accuracy in the results given by those algorithms is crucial. The surroundings of the organ to be segmented or registered can provide additional information that at the end improves the result. In this paper a novel algorithm to detect the organs that surround the liver is introduced. Even though our work is focused on the liver, the algorithm could be extended to other parts of the body. The algorithm has been tested in 24 clinical CT datasets. In addition to this, an example application is introduced for which the detection is a useful tool.
| Item Type: | Conference or Workshop Item |
|---|---|
| Erschienen: | 2014 |
| Creators: | Oyarzun Laura, Cristina ; Drechsler, Klaus ; Wesarg, Stefan |
| Type of entry: | Bibliographie |
| Title: | Anatomical Discovery: Finding Organs in the Neighborhood of the Liver |
| Language: | English |
| Date: | 2014 |
| Publisher: | Springer, Berlin, Heidelberg, New York |
| Series: | IFMBE Proceedings; 41 |
| Event Title: | XIII Mediterranean Conference on Medical and Biological Engineering and Computing |
| DOI: | 10.1007/978-3-319-00846-2_86 |
| Abstract: | Image segmentation and registration algorithms are fundamental to assist medical doctors for better treatment of the patients. To this end accuracy in the results given by those algorithms is crucial. The surroundings of the organ to be segmented or registered can provide additional information that at the end improves the result. In this paper a novel algorithm to detect the organs that surround the liver is introduced. Even though our work is focused on the liver, the algorithm could be extended to other parts of the body. The algorithm has been tested in 24 clinical CT datasets. In addition to this, an example application is introduced for which the detection is a useful tool. |
| Uncontrolled Keywords: | Business Field: Visual decision support, Research Area: Computer vision (CV), Medical imaging, Detection, Registration, Liver |
| Divisions: | 20 Department of Computer Science 20 Department of Computer Science > Interactive Graphics Systems |
| Date Deposited: | 12 Nov 2018 11:16 |
| Last Modified: | 12 Nov 2018 11:16 |
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