Down syndrome is one of the most common genetic disorders caused by chromosome abnormalities in humans. Among other physical characteristics, certain facial features are typically associated in people with Down syndrome. We investigate the problem of Down syndrome detection from a collection of face images. As the main contribution, a compact geometric descriptor is used to extract facial features from the images. Experiments are conducted on an available dataset to demonstrate the performance of the proposed methodology.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5726980 | PMC |
| http://dx.doi.org/10.1117/1.JMI.4.4.044008 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Spatiotemporal multi-feature fusion vehicle trajectory anomaly detection for intelligent transportation: An improved method combining autoencoders and dynamic Bayesian networks.
Accid Anal Prev
January 2025
School of Computer Science and Informatics, De Montfort University, Leicester LE1 9BH, UK.
With the continuous development of intelligent transportation systems, traffic safety has become a major societal concern, and vehicle trajectory anomaly detection technology has emerged as a crucial method to ensure safety. However, current technologies face significant challenges in handling spatiotemporal data and multi-feature fusion, including difficulties in big data processing, and have room for improvement in these areas. To address these issues, this paper proposes a novel method that combines autoencoders, Mahalanobis distance, and dynamic Bayesian networks for anomaly detection.
View Article and Find Full Text PDFAnalyzing the TotalSegmentator for facial feature removal in head CT scans.
Radiography (Lond)
January 2025
Department of Radiology, Charité Universitätsmedizin Berlin, Berlin, Germany; Berlin Institute of Health, Berlin, Germany.
Background: Facial recognition technology in medical imaging, particularly with head scans, poses privacy risks due to identifiable facial features. This study evaluates the use of facial recognition software in identifying facial features from head CT scans and explores a defacing pipeline using TotalSegmentator to reduce re-identification risks while preserving data integrity for research.
Methods: 1404 high-quality renderings from the UCLH EIT Stroke dataset, both with and without defacing were analysed.
Generation Victoria (GenV): protocol for a longitudinal birth cohort of Victorian children and their parents.
BMC Public Health
January 2025
Murdoch Children's Research Institute, 50 Flemington Road, Parkville, VIC, 3052, Australia.
Background: In a world confronted with new and connected challenges, novel strategies are needed to help children and adults achieve their full potential, to predict, prevent and treat disease, and to achieve equity in services and outcomes. Australia's Generation Victoria (GenV) cohorts are designed for multi-pronged discovery (what could improve outcomes?) and intervention research (what actually works, how much and for whom?). Here, we describe the key features of its protocol.
View Article and Find Full Text PDFPrenatal diagnosis of mucopolysaccharidosis type I on hepatosplenomegaly and coarse features: a case-report.
BMC Pregnancy Childbirth
January 2025
Department of Clinical Genetics, Rennes University Hospital, Rennes, France.
Background: Mucopolysaccharidosis type I (MPS I - IDUA gene) is a rare autosomal recessive lysosomal storage disorder. Clinical symptoms, including visceral overload, are progressive and typically begin postnatally. Descriptions of hepatosplenomegaly associated with lysosomal pathology are uncommon during the prenatal period.
View Article and Find Full Text PDFValidation of the Emotionally Congruent and Incongruent Face-Body Static Set (ECIFBSS).
Behav Res Methods
January 2025
Department of Psychology, University of Quebec at Trois-Rivières, Trois-Rivières, Canada.
Frequently, we perceive emotional information through multiple channels (e.g., face, voice, posture).
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!