Respiratory motion introduces uncertainties when planning and delivering radiotherapy for lung cancer patients. Cone-beam projections acquired in the treatment room could provide valuable information for building motion models, useful for gated treatment delivery or motion compensated reconstruction. We propose a method for estimating 3D+T respiratory motion from the 2D+T cone-beam projection sequence by including prior knowledge about the patient's breathing motion. Motion estimation is accomplished by maximizing the similarity of the projected view of a patient specific model to observed projections of the cone-beam sequence. This is done semi-globally, considering entire breathing cycles. Using realistic patient data, we show that the method is capable of good prediction of the internal patient motion from cone-beam data, even when confronted with interfractional changes in the breathing motion.
Vandemeulebroucke, J, Kybic, J, Clarysse, P & Sarrut, D 2009, Respiratory motion estimation from cone-beam projections using a prior model. in Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2009: 12th International Conference, London, UK, September 20-24, 2009, Proceedings, Part II. Image Processing, Computer Vision, Pattern Recognition, and Graphics, vol. 5762, Springer, pp. 365-372, MICCAI 2009 - 12th International Conference on Medical Image Computing and Computer-Assisted Intervention, London, United Kingdom, 20/09/09.
Vandemeulebroucke, J., Kybic, J., Clarysse, P., & Sarrut, D. (2009). Respiratory motion estimation from cone-beam projections using a prior model. In Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2009: 12th International Conference, London, UK, September 20-24, 2009, Proceedings, Part II (pp. 365-372). (Image Processing, Computer Vision, Pattern Recognition, and Graphics; Vol. 5762). Springer.
@inproceedings{035b9965507a47e187e2f03ef77a4dad,
title = "Respiratory motion estimation from cone-beam projections using a prior model",
abstract = "Respiratory motion introduces uncertainties when planning and delivering radiotherapy for lung cancer patients. Cone-beam projections acquired in the treatment room could provide valuable information for building motion models, useful for gated treatment delivery or motion compensated reconstruction. We propose a method for estimating 3D+T respiratory motion from the 2D+T cone-beam projection sequence by including prior knowledge about the patient's breathing motion. Motion estimation is accomplished by maximizing the similarity of the projected view of a patient specific model to observed projections of the cone-beam sequence. This is done semi-globally, considering entire breathing cycles. Using realistic patient data, we show that the method is capable of good prediction of the internal patient motion from cone-beam data, even when confronted with interfractional changes in the breathing motion.",
keywords = "Algorithms, Artifacts, Cone-Beam Computed Tomography, Humans, Imaging, Three-Dimensional, Lung, Movement, Radiographic Image Enhancement, Radiographic Image Interpretation, Computer-Assisted, Reproducibility of Results, Respiratory Mechanics, Sensitivity and Specificity",
author = "Jef Vandemeulebroucke and Jan Kybic and Patrick Clarysse and David Sarrut",
year = "2009",
language = "English",
isbn = "978-3-642-04270-6",
series = "Image Processing, Computer Vision, Pattern Recognition, and Graphics",
publisher = "Springer",
pages = "365--372",
booktitle = "Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2009",
note = "MICCAI 2009 - 12th International Conference on Medical Image Computing and Computer-Assisted Intervention ; Conference date: 20-09-2009 Through 24-09-2009",
}