Research in artificial intelligence for radiology and radiotherapy has recently become
increasingly reliant on the use of deep learning‐based algorithms. While the performance of …

Developers and users of artificial-intelligence-based tools for automatic contouring and
treatment planning in radiotherapy are expected to assess clinical acceptability of these …

Deep learning (DL) is one of the branches of artificial intelligence that has seen exponential
growth in recent years. The scientific community has focused its attention on DL due to its …

Auto-contouring could revolutionise future planning of radiotherapy treatment. The lack of
consensus on how to assess and validate auto-contouring systems currently limits clinical …

As data-driven science, artificial intelligence (AI) has paved a promising path toward an
evolving health system teeming with thrilling opportunities for precision oncology …

The pace of technological innovation over the past three decades has transformed the field
of radiotherapy into one of the most technologically intense disciplines in medicine …

Background and purpose Delineation of organs at risk (OARs), such as the bladder, rectum
and sigmoid, plays an important role in the delivery of optimal absorbed dose to the target …

Background Radiation treatment is considered an effective and the most common treatment
option for prostate cancer. The treatment planning process requires accurate and precise …

Background This paper attempts to conduct a systematic review and meta-analysis of deep
learning (DLs) models for cervical cancer CT image segmentation. Methods Relevant …

The complex and varied motion of the cervix–uterus target during external beam
radiotherapy (EBRT) underscores the clinical benefits afforded by adaptive radiotherapy …