Performance Evaluation of the Scale-Invariant Feature Transform in Different Modalities of Medical Image Registration
text-align left, line-height normal, text-indent px, ms-layout-grid-mode char, font-size px, font-family, Tiening Chen, Jianguang Zhuang sup, span · 2020
Recently, medical image registration processes are considered as a valuable assistant for the medical experts. The role of these processes arises from their ability to help the experts in the diagnosis, following up the diseases’ evolution, and deciding the necessary therapies regarding the patient’s condition. This evaluation method is based on feature point detection in reference images and corresponding point localization in registered floating images. For feature point detection, a 3D SIFT keypoint detector is applied to determine evaluation reference points. Therefore, the aim of this paper is to focus on the performance of SIFT in different modalities medical imaging feature points detection.