Introduction Gynecological cancers pose a significant threat to women worldwide, especially
those in resource-limited settings. Human analysis of images remains the primary method of …

Deep learning (DL) based approach aims to construct a full workflow solution for cervical
cancer with external beam radiation therapy (EBRT) and brachytherapy (BT). The purpose of …

Purpose Manual contour work for radiation treatment planning takes significant time to
ensure volumes are accurately delineated. The use of artificial intelligence with deep …

Purpose Our purpose was to investigate the influence of atlas library size and CT cross-slice
number on the accuracy and efficiency of the atlas-based auto-segmentation (ABAS) …

Objective Adaptive planning to accommodate anatomic changes during treatment often
requires repeated segmentation. In this study, prior patient‐specific data was integrateda …

Introduction Image segmentation is an important process for quantifying characteristics of
malignant bone lesions, but this task is challenging and laborious for radiologists. Deep …

Methods As of May 31, 2023, we conducted a comprehensive literature search on Google
Scholar, PubMed, and Web of Science using the following term combinations:“cervical …

Abstract Introduction In the Library‐of‐Plans (LoP) approach, correct plan selection is
essential for delivering radiotherapy treatment accurately. However, poor image quality of …

Simple Summary With recent progress in radiation therapy, patients with bone metastases
can be treated curatively, provided precise delineation of metastatic lesions is adequately …

Purpose The use of deep learning to auto-contour organs at risk (OARs) in gynecologic
radiation treatment is well established. Yet, there is limited data investigating the prospective …