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.
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| http://dx.doi.org/10.1109/EMBC46164.2021.9629944 | DOI Listing |
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