Pyramidal optical flow method-based lightweight monocular 3D vascular point cloud reconstruction

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...

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Main Authors: Liu, Chang, Zhang, Zhao, Lin, Huangxing, Hu, Yaqiong, Ng, Eyk, Chen, Dangzhao, Zhao, Lei, Lu, Yifan, Dai, Xin, Xu, Shipu, Liu, Xiaojun, Xie, Ning
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/145928
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1459282023-03-04T17:12:36Z Pyramidal optical flow method-based lightweight monocular 3D vascular point cloud reconstruction Liu, Chang Zhang, Zhao Lin, Huangxing Hu, Yaqiong Ng, Eyk Chen, Dangzhao Zhao, Lei Lu, Yifan Dai, Xin Xu, Shipu Liu, Xiaojun Xie, Ning School of Mechanical and Aerospace Engineering Engineering::Mechanical engineering 3D Point Cloud 3D Medical Digital Representation 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 version 2021-01-14T07:27:41Z 2021-01-14T07:27:41Z 2019 Journal Article Liu, C., Zhang, Z., Lin, H., Hu, Y., Ng, E., Chen, D., . . . Xie, N. (2019). Pyramidal optical flow method-based lightweight monocular 3D vascular point cloud reconstruction. IEEE Access, 7, 167420-167428. doi:10.1109/ACCESS.2019.2953818 2169-3536 0000-0002-1213-9814 0000-0003-4721-0905 0000-0002-3653-9871 0000-0002-1509-464X 0000-0001-9811-8995 0000-0001-8138-6125 0000-0002-7062-0374 0000-0002-5701-1080 0000-0002-3623-9211 0000-0001-7646-0503 0000-0001-6184-6200 0000-0003-2674-9426 https://hdl.handle.net/10356/145928 10.1109/ACCESS.2019.2953818 2-s2.0-85077548166 7 167420 167428 en IEEE Access © 2019 IEEE. This journal is 100% open access, which means that all content is freely available without charge to users or their institutions. All articles accepted after 12 June 2019 are published under a CC BY 4.0 license, and the author retains copyright. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, as long as proper attribution is given. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Mechanical engineering
3D Point Cloud
3D Medical Digital Representation
spellingShingle Engineering::Mechanical engineering
3D Point Cloud
3D Medical Digital Representation
Liu, Chang
Zhang, Zhao
Lin, Huangxing
Hu, Yaqiong
Ng, Eyk
Chen, Dangzhao
Zhao, Lei
Lu, Yifan
Dai, Xin
Xu, Shipu
Liu, Xiaojun
Xie, Ning
Pyramidal optical flow method-based lightweight monocular 3D vascular point cloud reconstruction
description 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.
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Liu, Chang
Zhang, Zhao
Lin, Huangxing
Hu, Yaqiong
Ng, Eyk
Chen, Dangzhao
Zhao, Lei
Lu, Yifan
Dai, Xin
Xu, Shipu
Liu, Xiaojun
Xie, Ning
format Article
author Liu, Chang
Zhang, Zhao
Lin, Huangxing
Hu, Yaqiong
Ng, Eyk
Chen, Dangzhao
Zhao, Lei
Lu, Yifan
Dai, Xin
Xu, Shipu
Liu, Xiaojun
Xie, Ning
author_sort Liu, Chang
title Pyramidal optical flow method-based lightweight monocular 3D vascular point cloud reconstruction
title_short Pyramidal optical flow method-based lightweight monocular 3D vascular point cloud reconstruction
title_full Pyramidal optical flow method-based lightweight monocular 3D vascular point cloud reconstruction
title_fullStr Pyramidal optical flow method-based lightweight monocular 3D vascular point cloud reconstruction
title_full_unstemmed Pyramidal optical flow method-based lightweight monocular 3D vascular point cloud reconstruction
title_sort pyramidal optical flow method-based lightweight monocular 3d vascular point cloud reconstruction
publishDate 2021
url https://hdl.handle.net/10356/145928
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