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...
Saved in:
Main Authors: | , , , , , , , , , , , |
---|---|
Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2021
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/145928 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-145928 |
---|---|
record_format |
dspace |
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 |
_version_ |
1759855046612221952 |