ID | 116678 |
Author |
Kawata, Yoshiki
Tokushima University
Tokushima University Educator and Researcher Directory
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Niki, Noboru
Tokushima University
Tokushima University Educator and Researcher Directory
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Sugiura, Toshihiko
Chiba University
Tanabe, Nobuhiro
Chiba University
Kusumoto, Masahiko
National Cancer Center Hospital East
Eguchi, Kenji
Teikyo University
Kaneko, Masahiro
Tokyo Health Service Association
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Keywords | Chronic thromboembolic pulmonary hypertension
computed tomography
computer aided diagnosis
CT lung screening
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Content Type |
Journal Article
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Description | Chronic thromboembolic pulmonary hypertension (CTEPH) is characterized by obstruction of the pulmonary vasculature by residual organized thrombi. A morphological abnormality inside mediastinum of CTEPH patient is enlargement of pulmonary artery. This paper presents an automated assessment of aortic and main pulmonary arterial diameters for predicting CTEPH in low-dose CT lung screening. The distinctive feature of our method is to segment aorta and main pulmonary artery using both of prior probability and vascular direction which were estimated from mediastinal vascular region using principal curvatures of four-dimensional hyper surface. The method was applied to two datasets, 64 low-dose CT scans of lung cancer screening and 19 normal-dose CT scans of CTEPH patients through the training phase with 121 low-dose CT scans. This paper demonstrates effectiveness of our method for predicting CTEPH in low-dose CT screening.
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Journal Title |
Proceedings of SPIE
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ISSN | 0277786X
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NCID | AA10619755
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Publisher | SPIE
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Volume | 10575
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Start Page | 105750X
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Published Date | 2018-02-27
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Remark | Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki, Toshihiko Sugiura, Nobuhiro Tanabe, Masahiko Kusumoto, Kenji Eguchi, and Masahiro Kaneko "Automated assessment of aortic and main pulmonary arterial diameters using model-based blood vessel segmentation for predicting chronic thromboembolic pulmonary hypertension in low-dose CT lung screening", Proc. SPIE 10575, Medical Imaging 2018: Computer-Aided Diagnosis, 105750X (27 February 2018); https://doi.org/10.1117/12.2293295
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Rights | Copyright 2018 Society of Photo-Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
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language |
eng
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departments |
Science and Technology
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