XAI Feature Detector for Ultrasound Feature Matching.

Journal: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Published Date:

Abstract

Feature matching is a crucial component of computer vision that has various applications. With the emergence of Computer-Aided Diagnosis (CAD), the need for feature matching has also emerged in the medical imaging field. In this paper, we proposed a novel algorithm using the Explainable Artificial Intelligence (XAI) [1] approach to achieve feature detection for ultrasound images based on the Deep Unfolding Super-resolution Network (USRNET). Based on the experimental results, our method shows higher interpretability and robustness than existing traditional feature extraction and matching algorithms. The proposed method provides a new insight for medical image processing, and may achieve better performance in the future with advancements of deep neural networks.

Authors

  • Zihao Wang
    Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
  • Hang Zhu
  • Yingnan Ma
  • Anup Basu
    Department of Computing Science, University of Alberta, Canada. Electronic address: basu@ualberta.ca.