Image Registration Algorithm for Sequence Pathology Slices Of Pulmonary Nodule

被引：0

作者：

Liu, Qianqian ^{[1
]}

Zhao, Gaofeng ^{[2
]}

Deng, Jicai ^{[1
]}

Xue, Qi ^{[1
]}

Hou, Weiyan ^{[1
]}

He, Yingzhe ^{[1
]}

机构：

[1] Zhengzhou Univ, Sch Informat Engn, Zhengzhou, Peoples R China

[2] Zhengzhou Univ, Affiliated Hosp 1, Zhengzhou, Peoples R China

来源：

2019 8TH INTERNATIONAL SYMPOSIUM ON NEXT GENERATION ELECTRONICS (ISNE) | 2019年

关键词：

pathological section images; image registration; pulmonary nodule; scale-invariant feature transform (SIFT); fast sparse coding (FSC); SIFT;

D O I：

10.1109/isne.2019.8896682

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页数：3

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