SPECT Reconstruction Algorithm Visualization Experimental Platform

Ning Li; Zhibiao Cheng; Jie Li; Junhai Wen

doi:10.1109/ICCT52962.2021.9658016

SPECT Reconstruction Algorithm Visualization Experimental Platform

Ning Li
, Zhibiao Cheng
, Jie Li
, Junhai Wen

School of Life Science

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

SPECT is an important nuclear medicine technology. Compared with imaging technologies such as ultrasound and CT, SPECT can obtain functional images. Therefore, SPECT plays an important role in clinical diagnosis of brain function and cardiovascular diseases, and has broad application prospects. However, factors such as noise interference, detector blur effects and attenuation problems will affect the reconstruction of SPECT images, so it is necessary to design algorithms to remove these interferences. The purpose of this article is to build a visual experimental platform based on these algorithms. For various reconstruction algorithms, modular design is carried out for the experimental platform to call. At the same time, it has also established an interface for users to use self-written algorithms to meet user needs and provide convenience for the updating of various algorithms.

Original language	English
Title of host publication	2021 IEEE 21st International Conference on Communication Technology, ICCT 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1017-1021
Number of pages	5
ISBN (Electronic)	9781665432061
DOIs	https://doi.org/10.1109/ICCT52962.2021.9658016
Publication status	Published - 2021
Event	21st IEEE International Conference on Communication Technology, ICCT 2021 - Tianjin, China Duration: 13 Oct 2021 → 16 Oct 2021

Publication series

Name	International Conference on Communication Technology Proceedings, ICCT
Volume	2021-October

Conference

Conference	21st IEEE International Conference on Communication Technology, ICCT 2021
Country/Territory	China
City	Tianjin
Period	13/10/21 → 16/10/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

SPECT
image reconstruction
plugin
visualization platform

Access to Document

10.1109/ICCT52962.2021.9658016

Cite this

Li, N., Cheng, Z., Li, J., & Wen, J. (2021). SPECT Reconstruction Algorithm Visualization Experimental Platform. In 2021 IEEE 21st International Conference on Communication Technology, ICCT 2021 (pp. 1017-1021). (International Conference on Communication Technology Proceedings, ICCT; Vol. 2021-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCT52962.2021.9658016

@inproceedings{8e938e71a15e4e17b78041ee7a00d499,

title = "SPECT Reconstruction Algorithm Visualization Experimental Platform",

abstract = "SPECT is an important nuclear medicine technology. Compared with imaging technologies such as ultrasound and CT, SPECT can obtain functional images. Therefore, SPECT plays an important role in clinical diagnosis of brain function and cardiovascular diseases, and has broad application prospects. However, factors such as noise interference, detector blur effects and attenuation problems will affect the reconstruction of SPECT images, so it is necessary to design algorithms to remove these interferences. The purpose of this article is to build a visual experimental platform based on these algorithms. For various reconstruction algorithms, modular design is carried out for the experimental platform to call. At the same time, it has also established an interface for users to use self-written algorithms to meet user needs and provide convenience for the updating of various algorithms.",

keywords = "SPECT, image reconstruction, plugin, visualization platform",

author = "Ning Li and Zhibiao Cheng and Jie Li and Junhai Wen",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 21st IEEE International Conference on Communication Technology, ICCT 2021 ; Conference date: 13-10-2021 Through 16-10-2021",

year = "2021",

doi = "10.1109/ICCT52962.2021.9658016",

language = "English",

series = "International Conference on Communication Technology Proceedings, ICCT",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1017--1021",

booktitle = "2021 IEEE 21st International Conference on Communication Technology, ICCT 2021",

address = "United States",

}

Li, N, Cheng, Z, Li, J & Wen, J 2021, SPECT Reconstruction Algorithm Visualization Experimental Platform. in 2021 IEEE 21st International Conference on Communication Technology, ICCT 2021. International Conference on Communication Technology Proceedings, ICCT, vol. 2021-October, Institute of Electrical and Electronics Engineers Inc., pp. 1017-1021, 21st IEEE International Conference on Communication Technology, ICCT 2021, Tianjin, China, 13/10/21. https://doi.org/10.1109/ICCT52962.2021.9658016

SPECT Reconstruction Algorithm Visualization Experimental Platform. / Li, Ning; Cheng, Zhibiao; Li, Jie et al.
2021 IEEE 21st International Conference on Communication Technology, ICCT 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 1017-1021 (International Conference on Communication Technology Proceedings, ICCT; Vol. 2021-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - SPECT Reconstruction Algorithm Visualization Experimental Platform

AU - Li, Ning

AU - Cheng, Zhibiao

AU - Li, Jie

AU - Wen, Junhai

PY - 2021

Y1 - 2021

N2 - SPECT is an important nuclear medicine technology. Compared with imaging technologies such as ultrasound and CT, SPECT can obtain functional images. Therefore, SPECT plays an important role in clinical diagnosis of brain function and cardiovascular diseases, and has broad application prospects. However, factors such as noise interference, detector blur effects and attenuation problems will affect the reconstruction of SPECT images, so it is necessary to design algorithms to remove these interferences. The purpose of this article is to build a visual experimental platform based on these algorithms. For various reconstruction algorithms, modular design is carried out for the experimental platform to call. At the same time, it has also established an interface for users to use self-written algorithms to meet user needs and provide convenience for the updating of various algorithms.

AB - SPECT is an important nuclear medicine technology. Compared with imaging technologies such as ultrasound and CT, SPECT can obtain functional images. Therefore, SPECT plays an important role in clinical diagnosis of brain function and cardiovascular diseases, and has broad application prospects. However, factors such as noise interference, detector blur effects and attenuation problems will affect the reconstruction of SPECT images, so it is necessary to design algorithms to remove these interferences. The purpose of this article is to build a visual experimental platform based on these algorithms. For various reconstruction algorithms, modular design is carried out for the experimental platform to call. At the same time, it has also established an interface for users to use self-written algorithms to meet user needs and provide convenience for the updating of various algorithms.

KW - SPECT

KW - image reconstruction

KW - plugin

KW - visualization platform

UR - https://www.scopus.com/pages/publications/85124388637

U2 - 10.1109/ICCT52962.2021.9658016

DO - 10.1109/ICCT52962.2021.9658016

M3 - Conference contribution

AN - SCOPUS:85124388637

T3 - International Conference on Communication Technology Proceedings, ICCT

SP - 1017

EP - 1021

BT - 2021 IEEE 21st International Conference on Communication Technology, ICCT 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 21st IEEE International Conference on Communication Technology, ICCT 2021

Y2 - 13 October 2021 through 16 October 2021

ER -

SPECT Reconstruction Algorithm Visualization Experimental Platform

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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