Abstract
Respiration motion state is an important indicator for disease diagnose in clinical practice. In this paper, we approach this problem with 4D CT rib cage images and target on identifying the end-inhalation and end-exhalation phrases. Observing that the motion of rib bones well reflect the respiration motion state, we transform this problem into a rib bone segmentation problem. Firstly, we propose a novel steerable filter enhanced level set method for rib bone segmentation. We formulate the level set segmentation problem as a variational optimization problem. To address the blurry edge issue, we enhance the image with the classic steerable filter. After that, by comparing the positions of rib bones in sequential frames, we present an criterion to determine the end-expiration and end-inspiration phrases. We validate our approach with real 4D CT rib cage images and demonstrate the effectiveness of our approach.
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Acknowledgement
This work was supported in part to Dr. Zhou by the Fundamental Research Funds for the Central Universities under contract No. WK2100060014 and WK2100060011 and the start-up funding from the University of Science and Technology of China under contract No. KY2100000036, and in part to Prof. Li by the National Science Foundation of China under contract No. 61272316.
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Xie, C., Zhou, W., Ding, W., Li, H., Li, W. (2016). Respiration Motion State Estimation on 4D CT Rib Cage Images. In: Tian, Q., Sebe, N., Qi, GJ., Huet, B., Hong, R., Liu, X. (eds) MultiMedia Modeling. MMM 2016. Lecture Notes in Computer Science(), vol 9516. Springer, Cham. https://doi.org/10.1007/978-3-319-27671-7_68
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DOI: https://doi.org/10.1007/978-3-319-27671-7_68
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