Pyramidal Optical Flow Method-Based Lightweight Monocular 3D Vascular Point Cloud Reconstruction

Chang Liu; Zhao Zhang; Huangxing Lin; Yaqiong Hu; Eyk Ng; Dangzhao Chen; Lei Zhao; Yifan Lu; Xin Dai; Shipu Xu; Xiaojun Liu; Ning Xie

doi:10.1109/ACCESS.2019.2953818

IEEE Access (Jan 2019)

Pyramidal Optical Flow Method-Based Lightweight Monocular 3D Vascular Point Cloud Reconstruction

Chang Liu,
Zhao Zhang,
Huangxing Lin,
Yaqiong Hu,
Eyk Ng,
Dangzhao Chen,
Lei Zhao,
Yifan Lu,
Xin Dai,
Shipu Xu,
Xiaojun Liu,
Ning Xie

Affiliations

Chang Liu: ORCiD; School of Information Technology, Nanchang Hangkong University, Nanchang, China
Zhao Zhang: ORCiD; School of Information Technology, Nanchang Hangkong University, Nanchang, China
Huangxing Lin: ORCiD; Fujian Key Laboratory of Sensing and Computing for Smart City, School of Informatics, Xiamen University, Xiamen, China
Yaqiong Hu: ORCiD; Department of Cardiology, Shanghai East Hospital, Shanghai, China
Eyk Ng: ORCiD; School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore
Dangzhao Chen: ORCiD; School of Information Technology, Nanchang Hangkong University, Nanchang, China
Lei Zhao: ORCiD; Center for Future Media, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
Yifan Lu: ORCiD; Center for Future Media, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
Xin Dai: ORCiD; School of Information Technology, Nanchang Hangkong University, Nanchang, China
Shipu Xu: ORCiD; Agricultural Information Institute of Science and Technology, Shanghai Academy of Agricultural Sciences, Shanghai, China
Xiaojun Liu: ORCiD; Mathematical and Information Engineering Department, Nanhu College of Jiaxing University, Jiaxing, China
Ning Xie: ORCiD; Center for Future Media, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China

DOI: https://doi.org/10.1109/ACCESS.2019.2953818
Journal volume & issue: Vol. 7
pp. 167420 – 167428

Abstract

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We propose a method for reconstructing a 3D point cloud of the organ model based on optical flow and take the 3D cardiovascular model reconstruction as an example. This optical-flow distribution based 3D point cloud reconstruction method is divided into four steps. Firstly, we employ the Coey filter to remove the noise points and improve the resolution of the raw images. Secondly, we implement the Shi-Tomasi method to extract the feature points from these filtered images. Thirdly, we remove the redundancy in the feature point set by the optical flow distributions. Finally, we converted the obtained feature points from 2D to 3D through the optical flow distribution and then reconstructed a 3D point cloud of the medical organ. With the help of our 3D representation, doctors and patients can view the 3D medical models on the Web. The final result on the Web shows the proposed method is feasible and superior.

Published in IEEE Access

ISSN: 2169-3536 (Online)
Publisher: IEEE
Country of publisher: United States
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639

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