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Abstract:
Introduction: Magnetic Resonance Imaging (MRI) is widely used in oncology for staging, tumor response assessment, and radiation therapy (RT) planning due to its ability to provide a wide range of soft tissue imaging contrast. These contrasts can be optimized by a variety of MR sequence parameter sets (SPS), which directly affect the image quality and efficiency of further image processing. Depending on the sequence and clinical objective, these SPS can include up to 30 individual parameters. Optimization of SPS for a specific clinical scenario is often performed manually, which can be time-consuming. Therefore, an automated sequence optimization process is preferred. In this study, we propose a framework for the automatic optimization of MRI sequences based on SPS that are directly applied on the scanner.
