Gao An1, Li Hong2, Xiao-Bing Zhou1, Qiong Yang3, Mei-Qing Li4, Xiang-Yang Tang5. 1. Department of Anatomy, University of South China, Hengyang, China. 2. Department of Anatomy, University of South China, Hengyang, China. Electronic address: 412160937@qq.com. 3. Department of Medical Imaging, University of South China, Hengyang, China. 4. Surgical Department of Second Affiliated Hospital, University of South China, Hengyang, China. 5. Department of Radiology & Imaging Sciences Emory-GaTech, Department of Biomedical Engineering, Emory School of Medicine, Emory University Atlanta, United States. Electronic address: Xiang_yang_Tang@163.com.
Abstract
OBJECTIVE: We investigated and compared the functionality of two 3D visualization software provided by a CT vendor and a third-party vendor, respectively. Using surgical anatomical measurement as baseline, we evaluated the accuracy of 3D visualization and verified their utility in computer-aided anatomical analysis. METHODS: The study cohort consisted of 50 adult cadavers fixed with the classical formaldehyde method. The computer-aided anatomical analysis was based on CT images (in DICOM format) acquired by helical scan with contrast enhancement, using a CT vendor provided 3D visualization workstation (Syngo) and a third-party 3D visualization software (Mimics) that was installed on a PC. Automated and semi-automated segmentations were utilized in the 3D visualization workstation and software, respectively. The functionality and efficiency of automated and semi-automated segmentation methods were compared. Using surgical anatomical measurement as a baseline, the accuracy of 3D visualization based on automated and semi-automated segmentations was quantitatively compared. RESULTS: In semi-automated segmentation, the Mimics 3D visualization software outperformed the Syngo 3D visualization workstation. No significant difference was observed in anatomical data measurement by the Syngo 3D visualization workstation and the Mimics 3D visualization software (P>0.05). CONCLUSIONS: Both the Syngo 3D visualization workstation provided by a CT vendor and the Mimics 3D visualization software by a third-party vendor possessed the needed functionality, efficiency and accuracy for computer-aided anatomical analysis.
OBJECTIVE: We investigated and compared the functionality of two 3D visualization software provided by a CT vendor and a third-party vendor, respectively. Using surgical anatomical measurement as baseline, we evaluated the accuracy of 3D visualization and verified their utility in computer-aided anatomical analysis. METHODS: The study cohort consisted of 50 adult cadavers fixed with the classical formaldehyde method. The computer-aided anatomical analysis was based on CT images (in DICOM format) acquired by helical scan with contrast enhancement, using a CT vendor provided 3D visualization workstation (Syngo) and a third-party 3D visualization software (Mimics) that was installed on a PC. Automated and semi-automated segmentations were utilized in the 3D visualization workstation and software, respectively. The functionality and efficiency of automated and semi-automated segmentation methods were compared. Using surgical anatomical measurement as a baseline, the accuracy of 3D visualization based on automated and semi-automated segmentations was quantitatively compared. RESULTS: In semi-automated segmentation, the Mimics 3D visualization software outperformed the Syngo 3D visualization workstation. No significant difference was observed in anatomical data measurement by the Syngo 3D visualization workstation and the Mimics 3D visualization software (P>0.05). CONCLUSIONS: Both the Syngo 3D visualization workstation provided by a CT vendor and the Mimics 3D visualization software by a third-party vendor possessed the needed functionality, efficiency and accuracy for computer-aided anatomical analysis.
Authors: Barbara E U Burkhardt; Nicholas K Brown; Jaclyn E Carberry; Marí Nieves Velasco Forte; Nicholas Byrne; Gerald Greil; Tarique Hussain; Animesh Tandon Journal: Int J Cardiovasc Imaging Date: 2019-06-15 Impact factor: 2.357
Authors: Kaiyan Qiu; Zichen Zhao; Ghazaleh Haghiashtiani; Shuang-Zhuang Guo; Mingyu He; Ruitao Su; Zhijie Zhu; Didarul B Bhuiyan; Paari Murugan; Fanben Meng; Sung Hyun Park; Chih-Chang Chu; Brenda M Ogle; Daniel A Saltzman; Badrinath R Konety; Robert M Sweet; Michael C McAlpine Journal: Adv Mater Technol Date: 2017-12-06