  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.
