CORDIS Project
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This project develops advanced statistical learning methods for medical imaging, particularly for tumor segmentation. It focuses on improving prediction accuracy by addressing the unique challenges of medical data, aiming for better outcomes in critical applications like radiation therapy.
Inference in medical imaging is an important step for disease diagnosis, tissue segmentation, alignment with an anatomical atlas, and a wide range of other applications.
However, imperfections in imaging sensors, physical limitations of imaging technologies, and variation in the human population mean that statistical methods are essential for high performance.
Statistical learning makes use of human provided ground truth to enable computers to automatically make predictions on future examples…
KATHOLIEKE UNIVERSITEIT LEUVEN
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