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Developing A Unified Facial Tissue Thickness Model from Neuromaging data for Sri Lankan Using Statistical Analysis and Image Processing Techniques

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dc.contributor.author Batuwitage, L.T.
dc.contributor.author Jayawardena, A.
dc.contributor.author Sandamini, H.
dc.contributor.author Rajapakse, R.N.
dc.contributor.author Karunaratna, D.D.
dc.contributor.author Vidanapathirana, M.
dc.contributor.author Pallewatte, A.
dc.date.accessioned 2018-11-19T09:57:50Z
dc.date.available 2018-11-19T09:57:50Z
dc.date.issued 2017
dc.identifier.citation Vidanapathirana, M. et al., (2017). "Developing A Unified Facial Tissue Thickness Model from Neuromaging data for Sri Lankan Using Statistical Analysis and Image Processing Techniques ", International Journal of Research - Granthaalayah, Vol.5 (7), pp. 354-362 en_US
dc.identifier.issn 2394-3629
dc.identifier.uri http://dr.lib.sjp.ac.lk/handle/123456789/7557
dc.description.abstract Facial soft tissue thickness (FSTT) is essential to forensic anthropologists for facial reconstruction- recreating a recognizable face from an unidentified skull and to plastic surgeons for treatment planning. Together with the age and sex of a person, the facial profile is related to facial soft tissue thickness, which is required for accurate facial reconstruction and recognition. Having such a facial profile in the national level is very important for a country since FSTT changes according to the geographical factors. In this paper we are presenting a review on literature associated with this topic describing the methods used for data collection, measuring FSTT and analyzing those values along with the method we are proposing to be followed in the research we are to conduct in the Sri Lankan context. en_US
dc.description.sponsorship Funded by University of Sri Jayawardenapura, Sri Lanka en_US
dc.language.iso en en_US
dc.publisher International Journal of Research- Granthaalayah en_US
dc.subject Facial Reconstruction; Ultrasound; CT; MRI; ANOVA; SPSS. en_US
dc.title Developing A Unified Facial Tissue Thickness Model from Neuromaging data for Sri Lankan Using Statistical Analysis and Image Processing Techniques en_US
dc.type Article en_US
dc.identifier.doi 10.5281/zenodo.839794 en_US


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