Comparative clinical evaluation of atlas and deep-learning-based auto-segmentation of organ structures in liver cancer - Ahn, Sang Hee; Yeo, Adam Unjin; Kim, Kwang Hyeon; Kim, Chankyu; Goh, Youngmoon; Cho, Shinhaeng; Lee, Se Byeong; Lim, Young Kyung; Kim, Haksoo; Shin, Dongho; Kim, Taeyoon; Kim, Tae Hyun; et al. (Radiation oncology (London, England), 2019)
Keywords: Accuracy; Aged; Artificial neural networks; Atlas-based auto-segmentation; Biomedical and Life Sciences; Biomedicine; Cable television broadcasting industry; Cancer; Cancer patients; Cancer Research; Cancer therapies; Care and treatment; Clinical Radiation Oncology; Comparative analysis; Computed tomography; Contouring; Convolution; Datasets; Deep convolution neural network (DCNN); Deep Learning; Deep-learning-based auto-segmentation; Female; Heart; Humans; Image contrast; Image processing; Image Processing, Computer-Assisted - methods; Image segmentation; Imaging; Kidneys; Libraries; Liver; Liver cancer; Liver Neoplasms - diagnostic imaging; Liver Neoplasms - radiotherapy; Machine learning; Male; Medical imaging; Medical imaging equipment; Methods; Metric space; Middle Aged; Neural networks; Neural Networks, Computer; Observer Variation; Oncology; Organs; Organs at Risk; Patients; Physicians; Radiation; Radiation (Physics); Radiation therapy; Radiology; Radiotherapy; Radiotherapy Planning, Computer-Assisted - methods; Reproducibility of Results; Republic of Korea; Software; Stomach; Tomography; Tomography, X-Ray Computed; Republic of Korea; United States; United Kingdom--UK; United States--US; Contouring; Deep convolution neural network (DCNN); Atlas-based auto-segmentation; Deep-learning-based auto-segmentation