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- W1534452426 abstract "X-ray computed tomography images (CT) are widely used in radiotherapy planning because they provide electronic densities of tissues of interest which are mandatory to a correct dose computation. Furthermore, the good spatial resolution and soft/hard tissues contrast allow precise target delineation. In this context of dose calculation and delivery, two challenging problems regarding CT images and radiotherapy are adressed here. First, we present a new automated approach to respiratory motion prediction. Respiratory motion leads to artifacts in the lower part of the lungs and blurs contours of tissues especially in thoracic and upper abdominal cases. Four-dimensional acquisitions allow accounting for this difficulty but at the expense of dosimetric considerations. On the other hand, the knowledge of the organs' motion during radiotherapy treatment is necessary (a) to a good conformation of the isodoses to the target contours and (b) to a sufficient protection of the organs at risk. In this study, we present a model-based method able to predict the internal movement of organs from CT images and external respiratory signals. A promising objective could be the improvement of dose computation and of real-time target tracking during treatment delivery. In the second part of this work, we present state-of-the-art image combination algorithms able to provide superior information when determining target contours from CT images. The aim is to extract pertinent information from both worlds of medical imaging, morphology and function, and to present them in a single image." @default.
- W1534452426 created "2016-06-24" @default.
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- W1534452426 date "2011-04-04" @default.
- W1534452426 modified "2023-10-16" @default.
- W1534452426 title "Image Processing Methods in CT for Radiotherapy Applications" @default.
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- W1534452426 doi "https://doi.org/10.5772/14613" @default.
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