A5018314596- Medical Image Segmentation Techniques
- Brain Tumor Detection and Classification
- Image Retrieval and Classification Techniques
- Parkinson's Disease Mechanisms and Treatments
- Neurological disorders and treatments
- Face and Expression Recognition
- Dementia and Cognitive Impairment Research
- Alzheimer's disease research and treatments
- Medical Imaging Techniques and Applications
- Functional Brain Connectivity Studies
- Spectroscopy and Chemometric Analyses
- Blind Source Separation Techniques
- Neural Networks and Applications
- AI in cancer detection
- Bayesian Methods and Mixture Models
- Gene expression and cancer classification
- Fractal and DNA sequence analysis
- Botulinum Toxin and Related Neurological Disorders
- Computational Drug Discovery Methods
- Artificial Intelligence in Healthcare
- Anomaly Detection Techniques and Applications
- Power Transformer Diagnostics and Insulation
- Cell Image Analysis Techniques
- Machine Learning and Data Classification
- Machine Learning in Bioinformatics
Universidad de Granada
2016-2025
Instituto Andaluz de Ciencias de la Tierra
2024
Universitat de Miguel Hernández d'Elx
2023
Centre for Addiction and Mental Health
2018
Hospital for Sick Children
2018
SickKids Foundation
2018
University of Toronto
2018
University of Cyprus
2018
University of Liège
2013-2017
University of Cambridge
2014
Deep Learning (DL), a groundbreaking branch of Machine (ML), has emerged as driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted complex non-linear artificial neural systems, excel at extracting high-level features from data. demonstrated human-level performance real-world tasks, including clinical diagnostics, unlocked solutions to previously intractable problems virtual agent design, robotics, genomics, neuroimaging, computer vision, industrial...
An automatic tool to assist the interpretation of single photon emission computed tomography (SPECT) and positron (PET) images for diagnosis Alzheimer's disease (AD) is demonstrated. The main problem be handled so-called small size sample, which consists having a number available compared large features. This faced by intensively reducing dimension feature space means principal component analysis (PCA). Our approach based on Bayesian classifiers, uses posteriori information determine in...
Purpose: In this work, an approach to computer aided diagnosis (CAD) system is proposed as a decision‐making aid in Parkinsonian syndrome (PS) detection. This tool, intended for physicians, entails fully automatic preprocessing, normalization, and classification procedures brain single‐photon emission computed tomography images. Methods: Ioflupane[ 123 I]FP‐CIT images are used provide vivo information of the dopamine transporter density. These preprocessed using automated template‐based...
An accurate and early diagnosis of the Alzheimer's disease (AD) is fundamental importance for patient's medical treatment. Single photon emission computed tomography (SPECT) images are commonly used by physicians to assist diagnosis. Presented a computer-assisted tool based in principal component analysis (PCA) dimensional reduction feature space approach support vector machine (SVM) classification method improving AD accuracy means SPECT images. The most relevant image features were...
This article presents a computer-aided diagnosis technique for improving the accuracy of early Alzheimer's disease (AD). Two hundred and ten 18F-FDG PET images from ADNI initiative [52 normal controls (NC), 114 mild cognitive impairment (MCI), 53 AD subjects] are studied.The proposed methodology is based on selection voxels interest using t-test posterior reduction feature dimension factor analysis. Factor loadings used as features three different classifiers: multivariate Gaussian mixture...
Purpose: An accurate and early diagnosis of Parkinsonian syndrome (PS) is nowadays a challenge. This includes several pathologies with similar symptoms (Parkinson's disease, multisystem atrophy, progressive supranuclear palsy, corticobasal degeneration others) which make the more difficult.123I-ioflupane allows to obtain in vivo images brain that can be used assist PS provides way improve its accuracy. Methods: In this paper, we show novel method automatically classify123I-ioflupane into two...
In last years, several approaches to develop an effective Computer-Aided-Diagnosis (CAD) system for Parkinson's Disease (PD) have been proposed. Most of these methods focused almost exclusively on brain images through the use Machine-Learning algorithms suitable characterize structural or functional patterns. Those patterns provide enough information about status and/or progression at intermediate and advanced stages Disease. Nevertheless this could be insufficient early pathology. The...
This paper presents a computer-aided diagnosis technique for improving the accuracy of early Alzheimer-type dementia. The proposed methodology is based on selection voxels which present Welch's t-test between both classes, normal and Alzheimer images, greater than given threshold. mean standard deviation intensity values are calculated selected voxels. They chosen as feature vectors two different classifiers: support vector machines with linear kernel classification trees. reaches 95% in task.
Although much research has been undertaken, the spatial patterns, developmental course, and sexual dimorphism of brain structure associated with autism remains enigmatic. One difficulties in investigating differences between sexes is small sample sizes available imaging datasets mixed sex. Thus, majority investigations have involved male samples, females somewhat overlooked. This paper deploys machine learning on partial least squares feature extraction to reveal regional individuals...
In recent years, several approaches to develop computer aided diagnosis (CAD) systems for dementia have been proposed. Some of these analyze neurological brain images by means machine learning algorithms in order find the patterns that characterize disorder, and a few combine imaging modalities improve diagnostic accuracy. However, they usually do not use neuropsychological testing data analysis. The purpose this work is measure advantages using only neuroimages as source CAD but also...
An early and differential diagnosis of parkinsonian syndromes still remains a challenge mainly due to the similarity their symptoms during onset disease. Recently, 18F-Desmethoxyfallypride (DMFP) has been suggested increase diagnostic precision as it is an effective radioligand that allows us analyze postsynaptic dopamine D2/3 receptors. Nevertheless, analysis these data poorly covered its use limited. In order address this challenge, paper shows novel model automatically distinguish...