Roentgen Diagnosis of Sex Based on Adult Skull Characteristics

Ceballos, Jorge; Rentschler, E. H.

doi:10.1148/70.1.55

Cited by 15 publications

(4 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The level of confidence of our results (99.99%) is far above those of Ceballos and Rentschler [ 19] and Giles and Elliot [20] in the human: the former predict the sex with a level of confidence of 80-90%, from measurements of radiological parameters; the latter, working on various discriminating measurements of the cranium, reach a level of confidence of 85%.…”

Section: Discussionsupporting

confidence: 42%

Computerized Tomographic Determination of the Cranial Volume of the Dog Applied to Racial and Sexual Differentiation

Regodón

Franco

Garin

et al. 1991

Cells Tissues Organs

View full text Add to dashboard Cite

The volume of the cranial cavity of 70 dogs (35 males and 35 females) has been determined in two breeds, the galgo greyhound and the pointer, by radiological techniques (computerized tomography; CT) and biostatistical methods. Each head was submitted to a complete series of transverse tomographic sections taken perpendicularly to the basilar plane, every 5 mm and with a thickness of 5 mm. There is a clear difference between the breeds and the two sexes, with a minimal confidence of 99.95%. The application of the method to fit zootechnical and/or osteoarcheological needs is emphasized.

show abstract

Section: Discussionsupporting

confidence: 42%

Computerized Tomographic Determination of the Cranial Volume of the Dog Applied to Racial and Sexual Differentiation

Regodón

Franco

Garin

et al. 1991

Cells Tissues Organs

View full text Add to dashboard Cite

show abstract

“…The sex determination by craniometry in lateral and/or PA cephalometric radiography has been studied in different populations, mostly with discriminant function analysis (DFA) than logical regression analysis (LRA). Ceballos and Rentschler[ 13 ] in 1958 utilized means and bar charts analyses for sex determination using four measurements obtained from PA cephalometric radiography of 200 Caucasian adult patients (100 males and 100 females) and achieved 88% accuracy. Townsend, Richards, and Carrol[ 7 ] in 1982 studied the DFA for sex determination in 15 measurements of both PA and lateral cephalometric radiographies of 80 Australian aboriginal adult patients (40 males and 40 females) and achieved 80% accuracy.…”

Section: Discussionmentioning

confidence: 99%

Applicability of the Ricketts' posteroanterior cephalometry for sex determination using logistic regression analysis in Hispano American Peruvians

Pérez¹,

Chávez

Ponce³

2016

J Forensic Dent Sci

View full text Add to dashboard Cite

Background:The Ricketts' posteroanterior (PA) cephalometry seems to be the most widely used and it has not been tested by multivariate statistics for sex determination.Objective:The objective was to determine the applicability of Ricketts' PA cephalometry for sex determination using the logistic regression analysis.Materials and Methods:The logistic models were estimated at distinct age cutoffs (all ages, 11 years, 13 years, and 15 years) in a database from 1,296 Hispano American Peruvians between 5 years and 44 years of age.Results:The logistic models were composed by six cephalometric measurements; the accuracy achieved by resubstitution varied between 60% and 70% and all the variables, with one exception, exhibited a direct relationship with the probability of being classified as male; the nasal width exhibited an indirect relationship.Conclusion:The maxillary and facial widths were present in all models and may represent a sexual dimorphism indicator. The accuracy found was lower than the literature and the Ricketts' PA cephalometry may not be adequate for sex determination. The indirect relationship of the nasal width in models with data from patients of 12 years of age or less may be a trait related to age or a characteristic in the studied population, which could be better studied and confirmed.

show abstract

“…This practice was important to paleoanthropologists, forensic pathologists and anatomists for the study and identification of bones from humans of unknown age, sex and racial group 22 . With the introduction of x-ray radiography, standardized views (cephalograms) allowed www.nature.com/scientificreports/ for more standardized measurements to aid in the study, diagnosis and management of trauma, orthognathic conditions and congenital deformity affecting the facial skeleton 23 . 3D computed tomography brought even more power to the study of anatomy, opening the door to reconstruction of images into a more intuitive 3D framework that can differentiate soft tissue from bone and that allows for more reproducible measurements.…”

Section: Related Workmentioning

confidence: 99%

Sex classification of 3D skull images using deep neural networks

Noel,

Fat,

Causey

et al. 2024

Sci Rep

View full text Add to dashboard Cite

Determining the fundamental characteristics that define a face as "feminine" or "masculine" has long fascinated anatomists and plastic surgeons, particularly those involved in aesthetic and gender-affirming surgery. Previous studies in this area have relied on manual measurements, comparative anatomy, and heuristic landmark-based feature extraction. In this study, we collected retrospectively at Cedars Sinai Medical Center (CSMC) a dataset of 98 skull samples, which is the first dataset of this kind of 3D medical imaging. We then evaluated the accuracy of multiple deep learning neural network architectures on sex classification with this dataset. Specifically, we evaluated methods representing three different 3D data modeling approaches: Resnet3D, PointNet++, and MeshNet. Despite the limited number of imaging samples, our testing results show that all three approaches achieve AUC scores above 0.9 after convergence. PointNet++ exhibits the highest accuracy, while MeshNet has the lowest. Our findings suggest that accuracy is not solely dependent on the sparsity of data representation but also on the architecture design, with MeshNet's lower accuracy likely due to the lack of a hierarchical structure for progressive data abstraction. Furthermore, we studied a problem related to sex determination, which is the analysis of the various morphological features that affect sex classification. We proposed and developed a new method based on morphological gradients to visualize features that influence model decision making. The method based on morphological gradients is an alternative to the standard saliency map, and the new method provides better visualization of feature importance. Our study is the first to develop and evaluate deep learning models for analyzing 3D facial skull images to identify imaging feature differences between individuals assigned male or female at birth. These findings may be useful for planning and evaluating craniofacial surgery, particularly gender-affirming procedures, such as facial feminization surgery.

show abstract

Roentgen Diagnosis of Sex Based on Adult Skull Characteristics

Cited by 15 publications

References 0 publications

Computerized Tomographic Determination of the Cranial Volume of the Dog Applied to Racial and Sexual Differentiation

Computerized Tomographic Determination of the Cranial Volume of the Dog Applied to Racial and Sexual Differentiation

Applicability of the Ricketts' posteroanterior cephalometry for sex determination using logistic regression analysis in Hispano American Peruvians

Sex classification of 3D skull images using deep neural networks

Contact Info

Product

Resources

About