Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/77711
Title: Geometric analysis method for sex determination using the first lumbar vertebra in a thai population
Authors: Yanumart Malatong
Patison Palee
Apichat Sinthubua
Y. Tohno
Pasuk Mahakkanukrauh
Authors: Yanumart Malatong
Patison Palee
Apichat Sinthubua
Y. Tohno
Pasuk Mahakkanukrauh
Keywords: Medicine
Issue Date: 1-Jan-2020
Abstract: Objective: The determination of sex is essential for forensic identification. Using the lumbar vertebra is helpful in cases when commonly used skeletal remains are incomplete. This study aimed to apply a geometric analysis method for determination of sex with the first lumbar vertebra in a Thai population. Materials and Methods: Two hundred first lumbar vertebra (L1) (100 males and 100 females) from Thai individuals of known sex ages 22 to 90 years (average age 60 years) were obtained from the Forensic Osteology Research Center, Faculty of Medicine, Chiang Mai University, Thailand. Geometric analysis was based on landmarks from the vertebral body, superior notch and inferior notch, that were digitized on photographed images. Determination of sex was obtained at a percentage of accuracy by k-mean clustering analysis. Intra and inter-observer errors were utilized for examination with this method. Results: The three features of the first lumbar vertebra for determination of sex were correctly estimated at 40.0-50.0% from the k-mean clustering. The accuracy in each feature of the vertebral body was 50%, the superior notch was 40% and in the inferior notch was 50%. Conclusion: Sex determination by using a geometric method which analyzed three features of the first lumbar vertebra were not useful for the determination of sex from only the shape of the variables. Future studies need to study the different shapes together with the sizes.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85118129592&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/77711
ISSN: 24363294
13412051
Appears in Collections:CMUL: Journal Articles

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