A deep learning algorithm to improve readers’ interpretation and speed of pancreatic cystic lesions on dual-phase enhanced CT

• Published in: Abdominal imaging Vol. 47; no. 6; pp. 2135 - 2147
• Main Authors: Wang, Xiheng, Sun, Zhaoyong, Xue, Huadan, Qu, Taiping, Cheng, Sihang, Li, Juan, Li, Yatong, Mao, Li, Li, Xiuli, Zhu, Liang, Li, Xiao, Zhang, Longjing, Jin, Zhengyu, Yu, Yizhou
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.06.2022; Springer Nature B.V
• Subjects: Accuracy; Algorithms; Computed tomography; Contrast media; Deep learning; Differential diagnosis; Differentiation; Feature extraction; Gastroenterology; Hepatology; Image enhancement; Imaging; Lesions; Machine learning; Medical diagnosis; Medicine; Medicine & Public Health; Pancreas; Radiology; Radiomics; Deep learning; Pancreatic cystic lesion; Computer-assisted; Diagnosis; Computed tomography

Purpose To develop a deep learning model (DLM) to improve readers’ interpretation and speed in the differentiation of pancreatic cystic lesions (PCLs) on dual-phase enhanced CT, and a low contrast media dose, external testing set validated the model. Materials and methods Dual-phase enhanced CT imag...