Purpose Deep learning can automate delineation in radiation therapy, reducing time and
variability. Yet, its efficacy varies across different institutions, scanners, or settings …

Purpose/Objective With the purported future of oncological care being precision medicine,
the hunt for predictive biomarkers has become a focal point. A potential source lies in …

Abstract Background and Purpose Auto-segmentation of organs at risk (OAR) in cancer
patients is essential for enhancing radiotherapy planning efficacy and reducing inter …

Precision oncology is increasingly becoming more accessible, with multiple models
available, although they are often not reproducible. This thesis explores the application of …

Radiomics is an emerging field in cancer research, however, the need for large amounts of
data and the lack of labeled and complete datasets raise significant challenges …