Structure specific atlas generation and its application to pancreas segmentation from contrasted abdominal CT volumes
Karasawa K, Kitasaka T, Oda M, Nimura Y, Hayashi Y, Fujiwara M, Misawa K, Rueckert D, Mori K (2016)
Publication Type: Conference contribution
Publication year: 2016
Journal
Publisher: Springer Verlag
Book Volume: 9601 LNCS
Pages Range: 47-56
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Germany, DEU
ISBN: 9783319420158
DOI: 10.1007/978-3-319-42016-5_5
Abstract
Patient-specific atlas is a key technology for the recognition of the human anatomy from 3D medical images. Automated recognition of the pancreas is one main issue for computer-assisted diagnosis and therapy systems in the abdomen because many diseases of the pancreas are not accompanied by noticeable symptoms. In patient-specific atlas generation, hierarchical and mosaicing methods have been proposed to cope with individual differences in the position, orientation, and shape of the pancreas. Even though segmentation accuracy was improved by these methods, it remains lower than for other abdominal organs, such as the liver and the kidneys. The location of the pancreas strongly correlates with the location of vasculature systems, especially the splenic vein. In this paper, we propose a new structure specific atlas generation method that considers the structural information in atlas generation. As for the structural information, we enhance the vasculature using a vesselness filter. Similar volumes in a training dataset with respect to the vasculature structure are selected and used for atlas generation. Using 150 cases of contrast-enhanced 3D abdominal CT volumes, our experiment improved the mis-segmentation of the surrounding organs or such soft tissues as the duodenum.
Involved external institutions
Nagoya University / 名古屋大学
Japan (JP)
Aichi Institute of Technology (AIT) / 愛知工業大学
Japan (JP)
Aichi Cancer Center Research Institute
Japan (JP)
Imperial College London / The Imperial College of Science, Technology and Medicine
United Kingdom (GB)
Japan (JP)
Aichi Institute of Technology (AIT) / 愛知工業大学
Japan (JP)
Aichi Cancer Center Research Institute
Japan (JP)
Imperial College London / The Imperial College of Science, Technology and Medicine
United Kingdom (GB)
How to cite
APA:
Karasawa, K., Kitasaka, T., Oda, M., Nimura, Y., Hayashi, Y., Fujiwara, M.,... Mori, K. (2016). Structure specific atlas generation and its application to pancreas segmentation from contrasted abdominal CT volumes. In Michael Kelm, Henning Müller, Bjoern Menze, Shaoting Zhang, Dimitris Metaxas, Georg Langs, Albert Montillo, Weidong Cai (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 47-56). Germany, DEU: Springer Verlag.
MLA:
Karasawa, Ken'Ichi, et al. "Structure specific atlas generation and its application to pancreas segmentation from contrasted abdominal CT volumes." Proceedings of the International Workshop on Medical Image Computing for Computer Assisted Intervention, 2015 MICCAI, Germany, DEU Ed. Michael Kelm, Henning Müller, Bjoern Menze, Shaoting Zhang, Dimitris Metaxas, Georg Langs, Albert Montillo, Weidong Cai, Springer Verlag, 2016. 47-56.
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