Recent advances and future perspectives of machine learning techniques offer promising
applications in medical imaging. Machine learning has the potential to improve different …

Background: Deformable image registration (DIR) is increasingly used in the field of
radiation therapy (RT) to account for anatomical deformations. The aims of this paper are to …

Purpose The delineation of the clinical target volume (CTV) is a crucial, laborious and
subjective step in cervical cancer radiotherapy. The aim of this study was to propose and …

Automation and artificial intelligence (AI) is already possible for many radiation therapy
planning and treatment processes with the aim of improving workflows and increasing …

Purpose To develop and evaluate the feasibility of deep learning approaches for MR‐based
treatment planning (deep MTP) in brain tumor radiation therapy. Methods and materials A …

Imaging modalities such as computed tomography (CT) and magnetic resonance imaging
(MRI) are widely used in diagnostics, clinical studies, and treatment planning. Automatic …

Purpose Contouring clinical target volume (CTV) from medical images is an essential step
for radiotherapy (RT) planning. Magnetic resonance imaging (MRI) is used as a standard …

Recent developments in magnetic resonance (MR) to synthetic computed tomography (sCT)
conversion have shown that treatment planning is possible without an initial planning CT …

Purpose To propose a novel deep-learning-based auto-segmentation model for CTV
delineation in cervical cancer and to evaluate whether it can perform comparably well to …

This review provides an overview of the current status of image registration for image guided
gynaecological brachytherapy including combination with external beam radiotherapy …