عنوان انگلیسی مقاله:
Deep Learning in Medical Ultrasound Analysis: A Review
ترجمه فارسی عنوان مقاله:
یادگیری عمیق در تجزیه و تحلیل سونوگرافی پزشکی: مرور
Sciencedirect - Elsevier - Engineering, 5 (2019) 261-275: doi:10:1016/j:eng:2018:11:020
Shengfeng Liu a, Yi Wanga, Xin Yang b, Baiying Lei a, Li Liu a, Shawn Xiang Li a, Dong Ni a,⇑, Tianfu Wang
Ultrasound (US) has become one of the most commonly performed imaging modalities in clinical practice.
It is a rapidly evolving technology with certain advantages and with unique challenges that include
low imaging quality and high variability. From the perspective of image analysis, it is essential to develop
advanced automatic US image analysis methods to assist in US diagnosis and/or to make such assessment
more objective and accurate. Deep learning has recently emerged as the leading machine learning tool in
various research fields, and especially in general imaging analysis and computer vision. Deep learning
also shows huge potential for various automatic US image analysis tasks. This review first briefly introduces
several popular deep learning architectures, and then summarizes and thoroughly discusses their
applications in various specific tasks in US image analysis, such as classification, detection, and segmentation.
Finally, the open challenges and potential trends of the future application of deep learning in medical
US image analysis are discussed.
Keywords: Deep learning | Medical ultrasound analysis | Classification | Segmentation | Detection