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## Quick Start Guide
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The easiest way to start is through the PorPy following Jupiter Notebook examples.
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The easiest way to start is through the PorPy following Jupiter Notebook examples:
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| Example File | Description |
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|------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| [imrt_dose_prediction.ipynb](https://github.com/PortPy-Project/PortPy/blob/master/examples/imrt_dose_prediction.ipynb) | Predicts 3D dose distribution using deep learning and converts it into a deliverable IMRT plan |
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| [vmat_global_optimal.ipynb](https://github.com/PortPy-Project/PortPy/blob/master/examples/vmat_global_optimal.ipynb) | Finds a globally optimal VMAT plan |
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| [beam_orientation_global_optimal.ipynb](https://github.com/PortPy-Project/PortPy/blob/master/examples/beam_orientation_global_optimal.ipynb) | Finds globally optimal beam angles for IMRT |
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| [dvh_constraint_global_optimal.ipynb](https://github.com/PortPy-Project/PortPy/blob/master/examples/dvh_constraint_global_optimal.ipynb) | Finds a globally optimal plan meeting Dose Volume Histogram (DVH) constraints |
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| [dvh_constraint_global_optimal.ipynb](https://github.com/PortPy-Project/PortPy/blob/master/examples/dvh_constraint_global_optimal.ipynb) | Finds a globally optimal plan meeting Dose Volume Histogram (DVH) constraints |

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