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      Sex Determination Using Human Sphenoid Sinus in a Northeast Iranian Population: A Discriminant Function Analysis

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          Abstract

          Statement of the Problem:

          Sex determination, using skeletal remains, is of paramount importance in forensic studies. The skull accounts for the most sexual dimorphism after the pelvis. Recent studies have shown that paranasal sinuses are valuable in sex determination and considering the location of the sphenoid sinus, the risk of traumatic injuries to this structure is low.

          Purpose:

          The present study aimed to evaluate the morphology of the sphenoid sinus and determine the validity of sphenoid sinus volume (SSV) in sex determination using cone beam computed tomography (CBCT) images.

          Materials and Method:

          In this cross-sectional retrospective study, CBCT images of 469 Iranian patients (186 male and 283 female), aged 24-45 years, were selected. The morphology of the sphenoid sinus was recorded. 3D Slicer software (4.10.0) was used to assess SSVs in coronal and axial planes. For data analysis, t-test, chi-square test, and discriminant function analysis (DFA) were performed using predictive analytics software (ver. 18.0).

          Results:

          The most common morphology of the sphenoid sinus in both genders was the sellar type (50.5%). SSV was significantly larger in males than in females ( p< 0.001). DFA showed that the capability of SSV in sex identification was 86.0% and 92.9% in males and females, respectively.

          Conclusion:

          The findings of this study suggest that SSV is a reliable variable in gender discrimination in a northeast Iranian population. However, since the morphology of the sphenoid sinus and sex were independent of each other, the morphology of the sphenoid sinus is not a suitable indicator for sex determination.

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          Most cited references41

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          3D Slicer as an image computing platform for the Quantitative Imaging Network.

          Quantitative analysis has tremendous but mostly unrealized potential in healthcare to support objective and accurate interpretation of the clinical imaging. In 2008, the National Cancer Institute began building the Quantitative Imaging Network (QIN) initiative with the goal of advancing quantitative imaging in the context of personalized therapy and evaluation of treatment response. Computerized analysis is an important component contributing to reproducibility and efficiency of the quantitative imaging techniques. The success of quantitative imaging is contingent on robust analysis methods and software tools to bring these methods from bench to bedside. 3D Slicer is a free open-source software application for medical image computing. As a clinical research tool, 3D Slicer is similar to a radiology workstation that supports versatile visualizations but also provides advanced functionality such as automated segmentation and registration for a variety of application domains. Unlike a typical radiology workstation, 3D Slicer is free and is not tied to specific hardware. As a programming platform, 3D Slicer facilitates translation and evaluation of the new quantitative methods by allowing the biomedical researcher to focus on the implementation of the algorithm and providing abstractions for the common tasks of data communication, visualization and user interface development. Compared to other tools that provide aspects of this functionality, 3D Slicer is fully open source and can be readily extended and redistributed. In addition, 3D Slicer is designed to facilitate the development of new functionality in the form of 3D Slicer extensions. In this paper, we present an overview of 3D Slicer as a platform for prototyping, development and evaluation of image analysis tools for clinical research applications. To illustrate the utility of the platform in the scope of QIN, we discuss several use cases of 3D Slicer by the existing QIN teams, and we elaborate on the future directions that can further facilitate development and validation of imaging biomarkers using 3D Slicer. Copyright © 2012 Elsevier Inc. All rights reserved.
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            Imaging software accuracy for 3-dimensional analysis of the upper airway.

            The aim of this study was to compare the precision and accuracy of 6 imaging software programs for measuring upper airway volumes in cone-beam computed tomography data.
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              Pituitary Adenoma Volumetry with 3D Slicer

              In this study, we present pituitary adenoma volumetry using the free and open source medical image computing platform for biomedical research: (3D) Slicer. Volumetric changes in cerebral pathologies like pituitary adenomas are a critical factor in treatment decisions by physicians and in general the volume is acquired manually. Therefore, manual slice-by-slice segmentations in magnetic resonance imaging (MRI) data, which have been obtained at regular intervals, are performed. In contrast to this manual time consuming slice-by-slice segmentation process Slicer is an alternative which can be significantly faster and less user intensive. In this contribution, we compare pure manual segmentations of ten pituitary adenomas with semi-automatic segmentations under Slicer. Thus, physicians drew the boundaries completely manually on a slice-by-slice basis and performed a Slicer-enhanced segmentation using the competitive region-growing based module of Slicer named GrowCut. Results showed that the time and user effort required for GrowCut-based segmentations were on average about thirty percent less than the pure manual segmentations. Furthermore, we calculated the Dice Similarity Coefficient (DSC) between the manual and the Slicer-based segmentations to proof that the two are comparable yielding an average DSC of 81.97±3.39%.
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                Author and article information

                Journal
                J Dent (Shiraz)
                J Dent (Shiraz)
                Journal of Dentistry
                Shiraz University of Medical Sciences (Iran )
                2345-6485
                2345-6418
                March 2023
                : 24
                : 1 Suppl
                : 95-102
                Affiliations
                [1 ] Graduate School for Health Sciences, Dept. of Restorative, Preventive and Pediatric Dentistry, School of Dental Medicine (ZMK Bern), University of Bern, Switzerland
                [2 ] Oral and Maxillofacial Diseases Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
                [3 ] Postgraduate Student, Dept. of Oral and Maxillofacial Radiology, School of Dentistry, Mashhad University of Medical Sciences, Mashhad, Iran
                [4 ] Dept. of Oral and Maxillofacial Radiology, School of Dentistry, Mashhad University of Medical Sciences, Mashhad, Iran
                Author notes
                Corresponding author: Bagherpour A, Dept. of Oral Radiology, Faculty of Dentistry & Dental Research Center, Mashhad University of Medical Sciences, Vakilabad Boulevard, Mashhad, Iran. Tel: +98-5138829501 Email: bagherpoura@ 123456mums.ac.ir , bagherpour.ali@ 123456gmail.com
                Article
                JDS-24-1.Suppl
                10.30476/dentjods.2022.92915.1685
                10084557
                9d0d5a05-dc72-4518-8d97-07b03a572722
                Copyright: © Journal of Dentistry

                This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License, ( http://creativecommons.org/licenses/by/4.0/ ) which permits reusers to copy and redistribute the material in any medium or format if the original work is properly cited, and attribution is given to the creator. The license also permits for commercial use.

                History
                : 8 January 2022
                : 7 February 2022
                : 9 November 2021
                Categories
                Original Article

                forensic anthropology, sex determination by skeleton, cone-beam computed tomography, discriminant analysis, iran

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