Hand Shape Modeling for the Mexican Population

Author(s):  
Graciela Rodríguez-Vega ◽  
Xiomara Penelope Zaldívar-Colado ◽  
Ulises Zaldívar-Colado ◽  
Enrique Javier De la Vega-Bustillos ◽  
Dora Aydee Rodríguez-Vega
2018 ◽  
Vol 14 (2) ◽  
Author(s):  
M.C. Ibarra

Abstract: To determine the frequency and distributionof dental anomalies of shape and numberin primary dentition. Methods: The study is retro-prolective, crosssectionaland descriptive. The sample was probabilistic,stratified for convenience by gender. Theclinical record of 1,568 patients was reviewed.These patients attended the Clinic of PediatricDentistry of FEBUAP during the period of 2012-2014, only 720 records of patients were includedin the study (321 girls and 399 boys) between theages of 1-10 years old, who provided complete,crisp radiographic studies with the presence ofdental anomalies of shape or number, the studywas divided into active and inactive patients.For inactive patients, photographs of x-rays withdental anomalies of shape and/or number weretaken. For cases with active patients, an interviewwith one of the parents was conducted andauthorization with informed consent was requested,also the child agreed to do a clinical examinationand take intraoral photographs. Results:A total of 63 children had anomalies (17girls and 46 boys). The total prevalence of dentalanomalies was 9%, of which 3.1% were (fusedand geminated teeth), 1.1% (agenesis) and 1.9%(supernumerary), 1.3% (supernumerary roots),0.27% (macrodontia), 0.11% (microdontia), andfinally 0.27% corresponded to (talon cusp). Conclusions: Although the prevalence of theseanomalies is not high, it is important to do a routineradiographic examination for early diagnosisand accordingly apply the correct preventivemeasures to establish the best treatment plan.


2017 ◽  
Author(s):  
Karen-Ivette Gutierrez-Aguirre ◽  
Maria-Luisa Lazo-de-la-Vega-Monroy ◽  
Yeniley Ruiz-Noa ◽  
Lorena-del-Rocio Ibarra-Reynoso ◽  
Juana-Rosalba Garcia-Ramirez ◽  
...  

2014 ◽  
Vol 1 (3) ◽  
pp. 8-17
Author(s):  
Shefali Sharma ◽  
◽  
Ashutosh Kumar Singh ◽  
Rajiv Saxena ◽  
◽  
...  

2003 ◽  
Author(s):  
M.A. Sanglikar ◽  
P. Koparkar ◽  
V.N. Joshi
Keyword(s):  

Author(s):  
Jing Qi ◽  
Kun Xu ◽  
Xilun Ding

AbstractHand segmentation is the initial step for hand posture recognition. To reduce the effect of variable illumination in hand segmentation step, a new CbCr-I component Gaussian mixture model (GMM) is proposed to detect the skin region. The hand region is selected as a region of interest from the image using the skin detection technique based on the presented CbCr-I component GMM and a new adaptive threshold. A new hand shape distribution feature described in polar coordinates is proposed to extract hand contour features to solve the false recognition problem in some shape-based methods and effectively recognize the hand posture in cases when different hand postures have the same number of outstretched fingers. A multiclass support vector machine classifier is utilized to recognize the hand posture. Experiments were carried out on our data set to verify the feasibility of the proposed method. The results showed the effectiveness of the proposed approach compared with other methods.


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