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Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Article DOI: 10.3791/61235-v • 07:15 min • August 16th, 2020
August 16th, 2020 •
1, 1, 2, 1, 1, 3, 1, 1
1Department of Radiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, 2Department of Medical Physics in Radiation Oncology, German Cancer Research Center, 3Department of Internal Medicine 3, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg

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Summary
Automatic Translation

This protocol was designed to train a machine learning algorithm to use a combination of imaging parameters derived from magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT) in a rat model of breast cancer bone metastases to detect early metastatic disease and predict subsequent progression to macrometastases.

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Machine Learning Algorithms Early Detection Bone Metastases Experimental Rat Model Imaging Parameters Machine Learning Algorithm Early Organ Colonization Multimodal Imaging Research DICOM Viewer DCE Sequence MRI Images Region Of Interest Baseline Range Analysis RStudio DCE Script File Imaging Features Template File Back Muscle
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