Intelligent sensing and monitoring : respiratory motion prediction for tumor following radiotherapy

• Autorzy: Ichiji K. , Homma N. , Sakai M. , Bukovsky I. , Zhang X. , Osanai M. , Abe M. , Sugita N. , Yoshizawa M.
• Języki publikacji: EN

Abstrakty

EN

This paper presents a medical application of the intelligent sensing and monitoring, a new lung tumor motion prediction method for tumor following radiation therapy. An essential core of the method is accurate estimation of complex fluctuation of time-varying periodical nature of lung tumor motion. Such estimation is achieved by using a novel multiple time-varying seasonal autoregressive (TVSAR) model in which several windows of different time-lengths are used to calculate correlation based fluctuation of periodic nature in the motion. The proposed method provides the prediction as a combination of those based on different window lengths. Multiple regression (MR), multilayer perceptron (MLP) and support vector regression (SVR) are used to combine and the prediction performances are evaluated by using clinical lung tumor motion. The proposed methods with the combined predictions showed high accurate prediction and are superior to the single different predictions. The average errors of MR, MLP, and SVR were 0.8455,0.8507, and 0.7530 mm at 0.5 s ahead, respectively. The results are clinically sufficient and thus clearly demonstrate that the proposed TVSAR with an appropriate combination method is useful for improving the prediction performance.

Słowa kluczowe

EN

intelligent sensing; monitoring; respiratory motion; tumor; radiotherapy; time-varying seasonal autoregressive model; TVSAR model; multiple regression; MR; multilayer perceptron; MLP; support vector regression; SVR

• Wydawca: University of Social Sciences
• Czasopismo: Journal of Artificial Intelligence and Soft Computing Research
• Rocznik: 2012
• Tom: Vol. 2, No. 4
• Strony: 331--342
• Opis fizyczny: Bibliogr. 17 poz., rys.

Twórcy

autor

Ichiji K.

• Graduate School of Engineering, Tohoku University, Sendai, Japan

autor

Homma N.

• Tohoku University Graduate School of Medicine, Sendai, Japan

autor

Sakai M.

• Center for Information Technology in Education, Tohoku University, Japan

autor

Bukovsky I.

• Czech Technical University in Prague, Prague, Czech Republic

autor

Zhang X.

• Tohoku University Graduate School of Medicine, Sendai, Japan

autor

Osanai M.

• Tohoku University Graduate School of Medicine, Sendai, Japan

autor

Abe M.

• Graduate School of Engineering, Tohoku University, Sendai, Japan

autor

Sugita N.

• Graduate School of Engineering, Tohoku University, Sendai, Japan

autor

Yoshizawa M.

• Cyberscience Center, Tohoku University, Sendai, Japan

Bibliografia

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