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Šárka Bejdová
Researcher at Charles University in Prague
Publications - 15
Citations - 203
Šárka Bejdová is an academic researcher from Charles University in Prague. The author has contributed to research in topics: Population & Sexual dimorphism. The author has an hindex of 6, co-authored 13 publications receiving 140 citations.
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Journal ArticleDOI
Variability in palatal shape and size in patients with bilateral complete cleft lip and palate assessed using dense surface model construction and 3D geometric morphometrics.
Šárka Bejdová,Václav Krajíček,Miroslav Peterka,Miroslav Peterka,Pavel Trefný,Jana Velemínská +5 more
TL;DR: A comparison of the mean shapes of the clefted and nonclefted groups showed that the BCLP palate is flatter and narrower, and the most notable size difference was found in the area between the maxilla and premaxilla.
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Changes in the sexual dimorphism of the human mandible during the last 1200 years in Central Europe.
TL;DR: This research supports earlier studies that have found that the degree and pattern of sexual dimorphism is population-specific and the factors regulating sexualDimorphism today may not be the same as those in the past.
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Sex estimation using external morphology of the frontal bone and frontal sinuses in a contemporary Czech population
TL;DR: This study focused on sex estimation using the form and shape of the external surface of the frontal bone with or without the inclusion of its sinuses, and found that the whole external frontal surface was significantly different between males and females.
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3-D shape analysis of palatal surface in patients with unilateral complete cleft lip and palate
TL;DR: The aim of this study was to evaluate palatal morphology and variability in patients with UCLP compared with Czech norms using methods of geometric morphometrics and found that the variability of palatal shape in UclP patients was greater than that in nonclefted palates.
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Advanced procedures for skull sex estimation using sexually dimorphic morphometric features.
TL;DR: An automated method based on a fully automatic algorithm applied on 3D models for extracting sex diagnostic morphometric features which are further processed by computer vision and machine learning algorithms is introduced.