Developments of thrombosis detection algorithm using the contrast enhanced CT images

Jun Oya; Hidenobu Suzuki; Yoshiki Kawata; Noboru Niki; Toshihiko Sugiura; Nobuhiro Tanabe; Yuichi Takiguchi; Koichiro Tatsumi

doi:10.1117/12.877934

9 March 2011 Developments of thrombosis detection algorithm using the contrast enhanced CT images

Jun Oya, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki, Toshihiko Sugiura, Nobuhiro Tanabe, Yuichi Takiguchi, Koichiro Tatsumi

Author Affiliations +

Proceedings Volume 7963, Medical Imaging 2011: Computer-Aided Diagnosis; 79632B (2011) https://doi.org/10.1117/12.877934
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States

Abstract

In the diagnosis of thrombosis with no specific clinic symptoms, diagnostic imaging plays a greater role. Particularly, contrast Enhanced CT is low invasive diagnostics, and the thrombus in the pulmonary artery can be detected as a low density without the contrast effect. Moreover, because describing the change of concentration in lung field and the decline in lung blood vessel shadow is also possible, it is indispensable to diagnose of thrombosis. As the image diagnosis support, it is necessary to classify the pulmonary artery and vein that relate to the thrombosis, and to analyze the lung blood vessel quantitatively. The technique for detecting the thrombosis by detecting the position of the thrombus has been proposed so far. In this study, it aims to focusing on the dilation of the main pulmonary artery and to detect the thrombosis. The effectiveness of the method is shown by measuring the pulmonary trunk diameter by using the extracted pulmonary artery from contrast Enhanced CT through semi-automated method, and comparing it with a normal case.

Citation Download Citation

Jun Oya, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki, Toshihiko Sugiura, Nobuhiro Tanabe, Yuichi Takiguchi, and Koichiro Tatsumi "Developments of thrombosis detection algorithm using the contrast enhanced CT images", Proc. SPIE 7963, Medical Imaging 2011: Computer-Aided Diagnosis, 79632B (9 March 2011); https://doi.org/10.1117/12.877934

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