A5020167052- Biometric Identification and Security
- Radiomics and Machine Learning in Medical Imaging
- Brain Tumor Detection and Classification
- AI in cancer detection
- COVID-19 diagnosis using AI
- Forensic and Genetic Research
- User Authentication and Security Systems
- Forensic Fingerprint Detection Methods
- Handwritten Text Recognition Techniques
- EEG and Brain-Computer Interfaces
- Gaze Tracking and Assistive Technology
- Medical Image Segmentation Techniques
- Ocular Disorders and Treatments
- Digital Media Forensic Detection
- Lung Cancer Diagnosis and Treatment
- Data Management and Algorithms
- Glaucoma and retinal disorders
- Semantic Web and Ontologies
- Advanced MRI Techniques and Applications
- Artificial Intelligence in Healthcare
- Advanced X-ray and CT Imaging
- Optical Imaging and Spectroscopy Techniques
- Dementia and Cognitive Impairment Research
- Dental Implant Techniques and Outcomes
- Face recognition and analysis
Cuban Neuroscience Center
2021-2024
Advanced Technologies Application Center
2013-2019
This article proposes an ontology-based topological representation of remote-sensing images. Semantics, especially related to the relationships between objects represented, are not explicit in images and this fact limits spatial analysis. Our aim is provide ontological definition relations image using Quadtree data structure for indexing. explicitly defined ontology allowing automatic interpretation representations obtained, taking into account increasing analytical capabilities. has been...
Iris segmentation under visible wavelengths (VWs) is a vital processing step for iris recognition systems operating ata-distance or in non-cooperative environments. In these scenarios the presence of various artefacts, e.g. occlusions specular reflections, as well out-of-focus blur represents significant challenge. The vast majority proposed algorithms VW aim at discriminating and noniris regions without taking into account variability that present non-iris region. this paper, we introduce...
Alzheimer's disease is the most common form of dementia that can cause a brain neurological disorder with progressive memory loss as result cell damage. Prevention and treatment key challenge in today's aging society. Accurate diagnosis plays an important role patient management, especially early stages disease, because awareness risk allows patients to undergo preventive measures even before damage occurs irreversible. Over years, techniques such statistical modeling or machine learning...
The prevalence of visual impairment around the world is rapidly increasing, causing large numbers people to wear glasses. Glasses are generally considered an important noise source in iris recognition; under objective metrics, they have recently been shown deteriorate sample quality near-infrared (NIR) ocular images (consequently impairing segmentation accuracy and biometric performance). Automatically robustly detecting glasses therefore one prerequisites for acquisition high samples. While...
Video-based eye image acquisition in the visible spectrum for iris recognition has taken great importance current context of extensive use video surveillance cameras and mobile devices.This modality can provide more information from capture region, but it is essential that images captured have a quality allows an effective process.In this work, approach presented.It based on scheme whose novelty possibility evaluating simultaneously with process capturing.A measure takes into account...
The reconstruction of electrophysiological sources within the brain is sensitive to constructed head model, which depends on positioning accuracy anatomical landmarks known as fiducials. In this work, we propose an algorithm for automatic detection fiducial EEG electrodes 3D human model. Our proposal combines a dimensional reduction approach with perspective projection from 2D object space; eye and ear in face image by two cascades classifiers geometric transformations obtain spatial...
The Covid-19 pandemic has caused the congestion of intensive therapies making it impossible for each to have a full-time radiology service. An indicator is necessary allow intensivists evaluate evolution patients in advanced state disease depending on degree involvement their lungs and severity chest X-ray images (CXR). We propose an algorithm grade affectation CXR diagnosed with COVID-19 disease. combines assessment image quality, digital processing deep learning segmentation lung tissues...