Optical Flow-Based Extraction of Breathing Signal from Cone Beam CT Projections

被引:0
作者
Sabah, Shafiya [1 ]
Dhou, Salam [1 ,2 ]
机构
[1] Amer Univ Sharjah, Biomed Engn Grad Program, POB 26666, Sharjah, U Arab Emirates
[2] Amer Univ Sharjah, Dept Comp Sci & Engn, POB 26666, Sharjah, U Arab Emirates
关键词
lung cancer; image-guided radiotherapy; respiratory motion; cone beam CT; PCA; optical flow; MOTION TRACKING; LUNG; TUMOR; RADIOTHERAPY; DIAPHRAGM; MARKERS;
D O I
10.3390/asi8010020
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Respiratory motion serves as a major challenge during treatment of lung cancer patients using radiotherapy. In this work, an image-based method is presented to extract a respiratory signal directly from Cone Beam CT (CBCT) projections. A dense optical-flow method is used to acquire motion vectors between successive projections in each dataset, followed by the extraction of the dominant motion pattern by application of linear kernel Principal Component Analysis (PCA). The effectiveness of the method was tested on three patient datasets and the extracted breathing signal was compared to a ground-truth signal. The average phase shift was observed to be 1.936 +/- 0.734 for patient 1, 1.185 +/- 0.781 for patient 2 and 1.537 +/- 0.93 for patient 3. Moreover, a 4D CBCT image was reconstructed, considering the respiratory signal extracted, using the proposed method, and compared to that reconstructed considering the ground-truth respiratory signal. Results showed that a minimal difference was found between the image reconstructed using the proposed method and the ground-truth in terms of clarity, motion artifacts and edge sharpness.
引用
收藏
页数:15
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