论文标题
超声图像中的功能匹配
Feature matching in Ultrasound images
论文作者
论文摘要
功能匹配是在不同图像中识别单个对象的重要技术。它可以帮助机器从多个角度构建对特定对象的识别。多年来，功能匹配一直在各种计算机视觉应用中使用，例如交通监视，自动驾驶和其他系统。随着计算机辅助诊断（CAD）的出现，医学成像领域也出现了功能匹配技术的需求。在本文中，我们提出了一种基于深度学习的方法，特别是用于超声图像。将根据现有方法对常规图像的出色结果进行检查。由于超声图像与许多字段中的常规图像不同，例如纹理，噪声类型和维度，因此将评估并优化传统方法以应用于超声图像。
Feature matching is an important technique to identify a single object in different images. It helps machines to construct recognition of a specific object from multiple perspectives. For years, feature matching has been commonly used in various computer vision applications, like traffic surveillance, self-driving, and other systems. With the arise of Computer-Aided Diagnosis(CAD), the need for feature matching techniques also emerges in the medical imaging field. In this paper, we present a deep learning-based method specially for ultrasound images. It will be examined against existing methods that have outstanding results on regular images. As the ultrasound images are different from regular images in many fields like texture, noise type, and dimension, traditional methods will be evaluated and optimized to be applied to ultrasound images.
