Advance of Thyroid Nodule Ultrasound Diagnosis Based on Deep Learning

The incidence of thyroid nodules is increasing rapidly worldwide. In order to reduce the burden on doctors and improve the accuracy of diagnosis, ultrasound imaging plays an important role in the diagnosis and follow-up of thyroid nodules. In recent years, artificial intelligence (AI) technology based on machine learning and deep learning has improved significantly. With the help of medical imaging screening tools, physicians can make clinical decisions about thyroid nodules more efficiently and provide the best protection for patients as early as possible. This paper mainly discusses the research progress of computer vision and related algorithms in ultrasonic imaging of thyroid nodules in recent years from the aspects of image preprocessing, detection and segmentation of focal areas, feature extraction, and identification of benign/malignant nodules.