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Dynamic Target Tracking Method Based on Medical Imaging
The cross fusion of rehabilitation medicine and computer graphics is becoming a research hotspot. Due to the problems of low definition and unobvious features of the initial video data of medical images, the initial data is filtered and enhanced by adding image preprocessing, including image rotatio...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9127387/ https://www.ncbi.nlm.nih.gov/pubmed/35620599 http://dx.doi.org/10.3389/fphys.2022.894282 |
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author | Qin, Guofeng Qin, Jiahao Xia, Qiufang Zou, Jianghuang Lin, Pengpeng Ren, Chengkun Wang, Ruihan |
author_facet | Qin, Guofeng Qin, Jiahao Xia, Qiufang Zou, Jianghuang Lin, Pengpeng Ren, Chengkun Wang, Ruihan |
author_sort | Qin, Guofeng |
collection | PubMed |
description | The cross fusion of rehabilitation medicine and computer graphics is becoming a research hotspot. Due to the problems of low definition and unobvious features of the initial video data of medical images, the initial data is filtered and enhanced by adding image preprocessing, including image rotation and contrast enhancement, in order to improve the performance of the tracking algorithm. For the moving barium meal, the discrete point tracking and improved inter frame difference method are proposed; for the position calibration of tissues and organs, the Kernel Correlation Filter (KCF) and Discriminative Scale Space Tracker (DSST) correlation filtering method and the corresponding multi-target tracking method are proposed, and the experimental results show that the tracking effect is better. The two algorithms modify each other to further improve the accuracy of calibration and tracking barium meal flow and soft tissue organ motion, and optimize the whole swallowing process of moving target tracking model. |
format | Online Article Text |
id | pubmed-9127387 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91273872022-05-25 Dynamic Target Tracking Method Based on Medical Imaging Qin, Guofeng Qin, Jiahao Xia, Qiufang Zou, Jianghuang Lin, Pengpeng Ren, Chengkun Wang, Ruihan Front Physiol Physiology The cross fusion of rehabilitation medicine and computer graphics is becoming a research hotspot. Due to the problems of low definition and unobvious features of the initial video data of medical images, the initial data is filtered and enhanced by adding image preprocessing, including image rotation and contrast enhancement, in order to improve the performance of the tracking algorithm. For the moving barium meal, the discrete point tracking and improved inter frame difference method are proposed; for the position calibration of tissues and organs, the Kernel Correlation Filter (KCF) and Discriminative Scale Space Tracker (DSST) correlation filtering method and the corresponding multi-target tracking method are proposed, and the experimental results show that the tracking effect is better. The two algorithms modify each other to further improve the accuracy of calibration and tracking barium meal flow and soft tissue organ motion, and optimize the whole swallowing process of moving target tracking model. Frontiers Media S.A. 2022-05-10 /pmc/articles/PMC9127387/ /pubmed/35620599 http://dx.doi.org/10.3389/fphys.2022.894282 Text en Copyright © 2022 Qin, Qin, Xia, Zou, Lin, Ren and Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Physiology Qin, Guofeng Qin, Jiahao Xia, Qiufang Zou, Jianghuang Lin, Pengpeng Ren, Chengkun Wang, Ruihan Dynamic Target Tracking Method Based on Medical Imaging |
title | Dynamic Target Tracking Method Based on Medical Imaging |
title_full | Dynamic Target Tracking Method Based on Medical Imaging |
title_fullStr | Dynamic Target Tracking Method Based on Medical Imaging |
title_full_unstemmed | Dynamic Target Tracking Method Based on Medical Imaging |
title_short | Dynamic Target Tracking Method Based on Medical Imaging |
title_sort | dynamic target tracking method based on medical imaging |
topic | Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9127387/ https://www.ncbi.nlm.nih.gov/pubmed/35620599 http://dx.doi.org/10.3389/fphys.2022.894282 |
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