Artificial intelligence in breast ultrasonography

• Published in: Ultrasonography (Seoul, Korea) Vol. 40; no. 2; pp. 183 - 190
• Main Authors: Kim, Jaeil, Kim, Hye Jung, Kim, Chanho, Kim, Won Hwa
• Format: Journal Article
• Language: English
• Published: Korea (South) Korean Society of Ultrasound in Medicine 01.04.2021; 대한초음파의학회
• Subjects: Algorithms; Annotations; Artificial intelligence; Automation; Breast cancer; breast diseases; breast neoplasm; Classification; convolutional neural network; Datasets; Decision making; Feasibility studies; Localization; Mammography; Medical imaging; Neural networks; Special Review of Artificial Intelligence (part 2); Ultrasonic imaging; ultrasonography; Womens health; Workloads; 방사선과학; Breast diseases; Artificial intelligence; Convolutional neural network; Ultrasonography; Breast neoplasm

Although breast ultrasonography is the mainstay modality for differentiating between benign and malignant breast masses, it has intrinsic problems with false positives and substantial interobserver variability. Artificial intelligence (AI), particularly with deep learning models, is expected to impr...