Application of 3D modeling and fusion technology of medical image data in image teaching
Abstract Background We combined anatomy with imaging, transformed the 2D information of various imaging techniques into 3D information, and form the assessment system of real medical imaging cases in order to make up for the deficiencies in the current teaching of the medical imaging technology stud...
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BMC
2021-04-01
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Series: | BMC Medical Education |
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Online Access: | https://doi.org/10.1186/s12909-021-02620-z |
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author | Quan Yuan Xiaomei Chen Jian Zhai Yadi Chen Qingxiang Liu Zhongxiao Tan Gao Chen Kangle Zhuang Jianying Zhang Xi Xu Di Qiang Xuefei Shao |
author_facet | Quan Yuan Xiaomei Chen Jian Zhai Yadi Chen Qingxiang Liu Zhongxiao Tan Gao Chen Kangle Zhuang Jianying Zhang Xi Xu Di Qiang Xuefei Shao |
author_sort | Quan Yuan |
collection | DOAJ |
description | Abstract Background We combined anatomy with imaging, transformed the 2D information of various imaging techniques into 3D information, and form the assessment system of real medical imaging cases in order to make up for the deficiencies in the current teaching of the medical imaging technology students. Methods A total of 460 medical imaging students were selected and randomly divided into two groups. The research group received the teaching of the fusion of the original CT and MR data 3D model and the original image combined with 3D anatomical image. CT and MRI data are imported through load DICOM of 3D slicer. Different tissues and organs are segmented by threshold and watershed algorithm of segment editor module. Models are exported through export / import models and label maps in segmentation. Save the NHDR file of the original data and Obj file of the corresponding model through save the NHDR and corresponding Obj files are loaded into probe 1.0 software. The software can give different colors to the three-dimensional models of different organs or tissues to display the stereo models and related data, and display the hook edges of organ models on coronal, sagittal and axial images. At the same time, annotation can be established in the corresponding anatomical position. Finally, it can be saved as a single file of Hwl, and the teaching can be opened at any time through the program of probe 1.0. Statistical analysis Academic self-efficacy scale and Self-directed learning ability scale was adopted by self-directed learning evaluation scale between two groups. Results Compare the theoretical scores and case analysis scores of the two groups. The scores of the study and control groups were significantly higher than those of the control group. Before the experiment, no significant difference was detected in the self-efficacy of learning ability and learning behavior between the two groups, while after the experiment, these differences between the two groups were statistically significan. Moreover, the learning ability self-efficacy and learning behavior of the two groups of students after the experiment was significantly higher than that before the experiment. The self-efficacy of the learning behavior of the control group was higher after the experiment than that before the experiment, albeit the difference was not statistically significant. Conclusions The modern, information-based and humanized experimental teaching mode will be constantly improved under the support of PACS system in order to optimize the medical imaging teaching activities for the development of modern medical education. |
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issn | 1472-6920 |
language | English |
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spelling | doaj.art-f4f4c0e5e37b44b4a8911d68abd19b342022-12-21T19:51:06ZengBMCBMC Medical Education1472-69202021-04-0121111010.1186/s12909-021-02620-zApplication of 3D modeling and fusion technology of medical image data in image teachingQuan Yuan0Xiaomei Chen1Jian Zhai2Yadi Chen3Qingxiang Liu4Zhongxiao Tan5Gao Chen6Kangle Zhuang7Jianying Zhang8Xi Xu9Di Qiang10Xuefei Shao11Department of Imaging, Yi-Ji Shan Hospital, Wannan Medical CollegeDepartment of Imaging, Yi-Ji Shan Hospital, Wannan Medical CollegeDepartment of Imaging, Yi-Ji Shan Hospital, Wannan Medical CollegeDepartment of Imaging, Yi-Ji Shan Hospital, Wannan Medical CollegeDepartment of Imaging, Yi-Ji Shan Hospital, Wannan Medical CollegeDepartment of Imaging, Yi-Ji Shan Hospital, Wannan Medical CollegeHewanlan digital S T CO.LTDHewanlan digital S T CO.LTDDepartment of Imaging, Yi-Ji Shan Hospital, Wannan Medical CollegeHewanlan digital S T CO.LTDDepartment of Imaging, Yi-Ji Shan Hospital, Wannan Medical CollegeDepartment of Imaging, Yi-Ji Shan Hospital, Wannan Medical CollegeAbstract Background We combined anatomy with imaging, transformed the 2D information of various imaging techniques into 3D information, and form the assessment system of real medical imaging cases in order to make up for the deficiencies in the current teaching of the medical imaging technology students. Methods A total of 460 medical imaging students were selected and randomly divided into two groups. The research group received the teaching of the fusion of the original CT and MR data 3D model and the original image combined with 3D anatomical image. CT and MRI data are imported through load DICOM of 3D slicer. Different tissues and organs are segmented by threshold and watershed algorithm of segment editor module. Models are exported through export / import models and label maps in segmentation. Save the NHDR file of the original data and Obj file of the corresponding model through save the NHDR and corresponding Obj files are loaded into probe 1.0 software. The software can give different colors to the three-dimensional models of different organs or tissues to display the stereo models and related data, and display the hook edges of organ models on coronal, sagittal and axial images. At the same time, annotation can be established in the corresponding anatomical position. Finally, it can be saved as a single file of Hwl, and the teaching can be opened at any time through the program of probe 1.0. Statistical analysis Academic self-efficacy scale and Self-directed learning ability scale was adopted by self-directed learning evaluation scale between two groups. Results Compare the theoretical scores and case analysis scores of the two groups. The scores of the study and control groups were significantly higher than those of the control group. Before the experiment, no significant difference was detected in the self-efficacy of learning ability and learning behavior between the two groups, while after the experiment, these differences between the two groups were statistically significan. Moreover, the learning ability self-efficacy and learning behavior of the two groups of students after the experiment was significantly higher than that before the experiment. The self-efficacy of the learning behavior of the control group was higher after the experiment than that before the experiment, albeit the difference was not statistically significant. Conclusions The modern, information-based and humanized experimental teaching mode will be constantly improved under the support of PACS system in order to optimize the medical imaging teaching activities for the development of modern medical education.https://doi.org/10.1186/s12909-021-02620-z3D modelingPACSMedical image;image teaching |
spellingShingle | Quan Yuan Xiaomei Chen Jian Zhai Yadi Chen Qingxiang Liu Zhongxiao Tan Gao Chen Kangle Zhuang Jianying Zhang Xi Xu Di Qiang Xuefei Shao Application of 3D modeling and fusion technology of medical image data in image teaching BMC Medical Education 3D modeling PACS Medical image;image teaching |
title | Application of 3D modeling and fusion technology of medical image data in image teaching |
title_full | Application of 3D modeling and fusion technology of medical image data in image teaching |
title_fullStr | Application of 3D modeling and fusion technology of medical image data in image teaching |
title_full_unstemmed | Application of 3D modeling and fusion technology of medical image data in image teaching |
title_short | Application of 3D modeling and fusion technology of medical image data in image teaching |
title_sort | application of 3d modeling and fusion technology of medical image data in image teaching |
topic | 3D modeling PACS Medical image;image teaching |
url | https://doi.org/10.1186/s12909-021-02620-z |
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