Deep learning-based ultrasonic dynamic video detection and segmentation of thyroid gland and its surrounding cervical soft tissues.

Journal: Medical physics
Published Date: Nov 29, 2021

Abstract

BACKGROUND: The prevalence of thyroid diseases has been increasing year by year. In this study, we established and validated a deep learning method (Cascade region-based convolutional neural network, R-CNN) based on ultrasound videos for automatic detection and segmentation of the thyroid gland and its surrounding tissues in order to reduce the workload of radiologists and improve the detection and diagnosis rate of thyroid disease.

Authors

  • Hongxia Luo
    Department of Ultrasonic Diagnosis, Shenzhen Maternity and Child Healthcare Hospital, Cheeloo College of Medicine, Shandong University, Shenzhen, Guangdong, 518000, China.
  • Laifa Ma
    The College of Computer Science and Electronic Engineering, Hunan University, Changsha, Hunan, 410082, China.
  • Xiangqiong Wu
    The College of Computer Science and Electronic Engineering, Hunan University, Changsha, Hunan, 410082, China.
  • Guanghua Tan
  • Hui Zhu
  • Senmin Wu
    Department of Ultrasonic Diagnosis, The Second Affiliated Hospital and Yuying Children's Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, 325000, China.
  • Kenli Li
    College of Computer Science and Electronic Engineering & National Supercomputer Centre in Changsha, Hunan University, Changsha, China.
  • Yan Yang
    Department of Endocrinology and Metabolism, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
  • Shengli Li

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