3D Reconstruction Method based on Medical Image Feature Point Matching-Reference-Cited by-同舟云学术

3D Reconstruction Method based on Medical Image Feature Point Matching

Published:2022-08-12 Issue: Volume:2022 Page:1-11
ISSN:1748-6718
Container-title:Computational and Mathematical Methods in Medicine
language:en
Short-container-title:Computational and Mathematical Methods in Medicine

Author:

Han Jing¹^ORCID,Cao Yankun²^ORCID,Xu Lina³^ORCID,Liang Wei⁴^ORCID,Bo Qiyu⁵^ORCID,Wang JianLei⁶^ORCID,Wang Chun⁶^ORCID,Kou Qiqi⁷,Liu Zhi⁸^ORCID,Cheng Deqiang¹^ORCID

Affiliation:

1. School of Information and Control Engineering, China University of Mining and Technology, Jiangsu 221116, China

2. School of Software, Shandong University, Jinan 250101, China

3. School of Computer Science and Technology, Shandong Jianzhu University, Jinan 250012, China

4. Qilu University of Technology, Jinan 250353, China

5. Qilu Hospital of Shandong University, Jinan 250012, China

6. Optical Advanced Research Center, Shandong University, Qingdao 266237, China

7. School of Computer Science and Technology, China University of Mining and Technology, Jiangsu 221116, China

8. School of Information Science and Engineering, Shandong University, Qingdao 266237, China

Abstract

Medical 3D image reconstruction is an important image processing step in medical image analysis. How to speed up the speed while improving the accuracy in 3D reconstruction is an important issue. To solve this problem, this paper proposes a 3D reconstruction method based on image feature point matching. By improving SIFT, the initial matching of feature points is realized by using the neighborhood voting method, and then the initial matching points are optimized by the improved RANSAC algorithm, and a new SFM reconstruction method is obtained. The experimental results show that the feature matching rate of this algorithm on Fountain data is 95.42% and the matching speed is 4.751 s. It can be seen that this algorithm can shorten the reconstruction time and obtain sparse point clouds with more reasonable distribution and better reconstruction effect.

Funder

Major Scientific and Technological Innovation Project of Shandong Province

Publisher

Hindawi Limited

Subject

Applied Mathematics,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation,General Medicine

Link

http://downloads.hindawi.com/journals/cmmm/2022/9052751.pdf

Reference20 articles.

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