Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered
data with nuanced decision making. Cancer offers a unique context for medical decisions …

Recent years have witnessed widespread adoption of machine learning (ML)/deep learning
(DL) techniques due to their superior performance for a variety of healthcare applications …

Manual image segmentation is a time-consuming task routinely performed in radiotherapy to
identify each patient's targets and anatomical structures. The efficacy and safety of the …

Background and purpose Delineation of clinical target volumes (CTVs) is a weak link in
radiation therapy (RT), and large inter-observer variation is seen in breast cancer patients …

PURPOSE: Cardiac toxicity is an important sequela of breast radiotherapy. However, the
relationship between dose to cardiac structures and subsequent toxicity has not been well …

The heavy global burden and mortality of breast cancer emphasize the importance of early
diagnosis and treatment. Imaging detection is one of the main tools used in clinical practice …

Due to rapid advances in radiation therapy (RT), especially image guidance and treatment
adaptation, a fast and accurate segmentation of medical images is a very important part of …

Purpose This study quantifies variation in radiation treatment plan quality for plans
generated by a population of treatment planners given very specific plan objectives …

Purpose To train and evaluate a very deep dilated residual network (DD-ResNet) for fast
and consistent auto-segmentation of the clinical target volume (CTV) for breast cancer (BC) …

Purpose/Objective Lymphedema after breast cancer treatment can be an irreversible
condition with a negative impact on quality of life. The goal of this study was to identify …