Image Registration Algorithm for Sequence Pathology Slices Of Pulmonary Nodule

Qianqian Liu, Gaofeng Zhao, Jicai Deng, Q. Xue, Weiyan Hou, Yingzhe He
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引用次数: 1

Abstract

Registration of pathological section images is an important part of three-dimensional reconstruction of sections. In this paper, a registration method was proposed to solve the problem of mismatching of pathological section images of pulmonary nodules. Firstly, rough matching is performed, and the feature points are extracted according to the scale-invariant feature transform (SIFT) algorithm. Then fast sparse coding (FSC) is used for fine matching to eliminate mismatched pairs. The algorithm presented in this paper is applied to the registration between sequence sections of pulmonary nodules. The experimental results show that the algorithm can effectively find more matching point pairs, accurately remove the false matching point pairs, and significantly improve the registration accuracy.
肺结节序列病理切片图像配准算法
病理切片图像的配准是切片三维重建的重要组成部分。针对肺结节病理切片图像的不匹配问题,提出了一种配准方法。首先进行粗匹配,根据尺度不变特征变换(SIFT)算法提取特征点;然后采用快速稀疏编码(FSC)进行精细匹配,消除不匹配对。将本文提出的算法应用于肺结节序列切片间的配准。实验结果表明,该算法能有效地找到更多的匹配点对,准确去除虚假匹配点对,显著提高配准精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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