Forensic Identification from Three-Dimensional Sphenoid Sinus Images Using the Iterative Closest Point Algorithm.
Forensic identification of human remains is crucial for legal, humanitarian, and civil reasons. Wide heterogeneity in sphenoid sinus morphology can be used for personal identification. This study aimed to propose a new protocol for personal identification based on three-dimensional (3D) reconstructi...
| Publicado en: | Journal of Digital Imaging Vol. 35; no. 4; pp. 1034 - 1041 |
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| Autores principales: | , , , , , , , |
| Formato: | diagnostic images equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Aug2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=159195608&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 159195608 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Aug2022 vid: 35 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 159195608 156098495 159195608 159195608 10.1007/s10278-021-00572-w 159195608 ppf: 1034 ppct: 7 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Forensic Identification from Three-Dimensional Sphenoid Sinus Images Using the Iterative Closest Point Algorithm. aug: au: Dong, Xiaoai Fan, Fei Wu, Wei Wen, Hanjie Chen, Hu Zhang, Kui Zhang, Ji Deng, Zhenhua affil: West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, 610041, Chengdu, Sichuan, People's Republic of China sug: subj: Imaging, Three-Dimensional Sphenoid Sinus Algorithms Forensic Anthropology Image Processing, Computer Assisted Methods Tomography, Spiral Computed Human Male Female Retrospective Design Record Review Cadaver Descriptive Statistics Male Female ab: Forensic identification of human remains is crucial for legal, humanitarian, and civil reasons. Wide heterogeneity in sphenoid sinus morphology can be used for personal identification. This study aimed to propose a new protocol for personal identification based on three-dimensional (3D) reconstruction of sphenoid sinus CT images using Iterative Closest Point (ICP) algorithm. Seven hundred thirty-two patients which consisted of 348 females and 384 males were retrospectively included. The study sample includes 732 previous images as a source point set and 743 later ones as a scene target set. The sphenoid sinus computed tomography (CT) images were processed on a workstation (Dolphin imaging) to obtain 3D images and stored as a file format of Stereo lithography (.STL). Then, a Python library vtkplotter was used to transform the STL format to PLY format, which was adapted to Point Cloud Library (PCL). The ICP algorithm was used for point clouds matching. The metric Rank-N recognition rate was used for evaluation. The scene target set of 743 individuals was compared with the source point set of 732 individual models and achieved Rank-1 accuracy of 96.24%, Rank-2 accuracy of 99.73%, and Rank-3 accuracy of 100%. Our results indicated that the 3D point cloud registration of sphenoid sinuses was useful for assessing personal identification in forensic contexts. pubtype: Academic Journal doctype: diagnostic images equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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