Bioengineering and Biomedical Signal and Image Processing

Name: Bioengineering and Biomedical Signal and Image Processing | First International Conference, BIOMESIP 2021, Meloneras, Gran Canaria, Spain, July 19-21, 2021, Proceedings
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First International Conference, BIOMESIP 2021, Meloneras, Gran Canaria, Spain, July 19-21, 2021, Proceedings

Ignacio Rojas Daniel Castillo-Secilla Luis Javier Herrera Héctor Pomares(Herausgeber*in)

Springer (Verlag)

Erschienen am 8. Oktober 2021

XVIII, 517 Seiten

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978-3-030-88163-4 (ISBN)

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Inhalt

Intro
Preface
Organization
Contents
Biomedical Applications in Molecular, Structural, and Functional Imaging
Image Motion Correction of GATE Simulation in Dedicated PET Scanner with Open Geometry
1 Introduction
2 Materials and Methods
2.1 PET System and GATE Simulation
2.2 XCAT Phantom
2.3 EMAF Algorithm
2.4 Parameter Settings
2.5 Performance Metrics
3 Results and Discussion
4 Conclusions
5 Acronyms
References
Optimizing Photoacoustic Tomography: Lymphatic Drainage from the Brain in Pigmented Mice
1 Introduction
2 Methods
2.1 Animal Model
2.2 Contrast Agent
2.3 Photoacoustic Imaging System
2.4 Multispectral Unmixing of Chromophore Distributions
3 Results
4 Conclusion
References
Biomedical Computing
Relationships Between Vertical Jump and Composite Indices of Femoral Neck Strength in a Group of Young Women
1 Introduction
2 Material and Methods
2.1 Subjects and Study Design
2.2 Anthropometrics
2.3 Bone Variables
2.4 Vertical Jump
2.5 Statistical Analysis
3 Results
3.1 Clinical Characteristics and Bone Data of the Study Population
3.2 Correlations Between Clinical Characteristics and Bone Variables
3.3 Multiple Linear Regressions
4 Discussion
5 Conclusion
References
Automatic Classification of Valve Diseases Through Natural Language Processing in Spanish and Active Learning
1 Introduction
2 Methods
2.1 Corpus
2.2 Development of the Natural Language Processing System
2.3 Evaluation Metrics
2.4 Software and Open Source.
3 Results
3.1 Frequency of Valvulopathies in Echocardiographic Reports
3.2 Model Adjustment
3.3 Model Performance (External Validation)
3.4 Deployment of the System in a Free Demo and Active Learning
4 Discussion
5 Conclusions
References
Biomedical Signal Measurement, Acquisition and Processing
Automated Annotation of Valence and Arousal During Cognitive Activity
1 Introduction
2 Method
2.1 Overall Concept
2.2 Resources Required
2.3 Implementation
3 Experimental Setup
3.1 Feature Set
3.2 Detection
3.3 Performance Metrics
4 Results
4.1 Detection Performance Evaluation
4.2 Automatically Generated Tags
5 Conclusion
References
Focal and Generalized Seizures Distinction by Rebalancing Class Data and Random Forest Classification
1 Introduction
2 Materials and Methods
2.1 Database
2.2 The Proposed Method
3 Experimental Results
4 Conclusion
References
Event Related Potential Analysis Using Machine Learning to Predict Diagnostic Outcome of Autism Spectrum Disorder
1 Introduction
2 Methods and Materials
2.1 Participants
2.2 ERP Procedure
2.3 ERP Pre-processing
2.4 ERP Features Extraction and Selection
2.5 Classification Procedure
3 Results
4 Discussion and Limitation
References
Natural Cellulosic Fiber Reinforced Bio-Epoxy Based Composites and Their Mechanical Properties
1 Introduction
2 Materials and Methods
2.1 Materials
2.2 Methods
3 Results and Discussion
3.1 Morphological Analysis by Scanning Electron Microscopy (SEM)
3.2 Mechanical Properties
4 Conclusions
References
Modelling Brain Connectivity Networks by Graph Embedding for Dyslexia Diagnosis
1 Introduction
2 Materials and Methods
2.1 Database and Stimulus
2.2 Signal Prepocessing
2.3 Phase-Amplitude Coupling (PAC)
2.4 Connectivity Estimation by Phase-Amplitude Coupling
2.5 Graph Embedding
2.6 Classification
3 Results
4 Conclusions and Future Work
References
Causal Coupling of Low Frequency Oscillations During Movement Imagination - A Multimodal Study
1 Introduction
2 Material and Methods
3 Results
4 Discussion
References
Methodological Approaches to the Comparison of Left Ventricular Stroke Volume Values Measured by Ultrasonic Technique or Estimated via Transfer Functions
1 Introduction
2 Methods
2.1 LVSV and Arterial Pressure Data Obtaining
2.2 Calculation of TF
2.3 Statistical Analysis
3 Results
4 Conclusions
References
Investigation of Gastroparesis Using Multichannel Electro Gastro Gram - A Study
1 Introduction
2 Histroy
3 Procedures for Diagnosis of Gastroparesis
3.1 Esophagogastroduodenoscopy
3.2 GI Radiography
3.3 Gastric Myo - Electrical Activity
4 Methodology
5 Study of Electrogastrography
5.1 Electrogastrography - Recording
5.2 Patient Preparation
5.3 Placement of Electrodes
5.4 Patient State of Recording Signal
5.5 Recording Duration
5.6 Gastric Signals
5.7 Flaws in EGG Recording
5.8 EGG Signal Analysis
6 Other Disorders
7 Summary
8 Conclusion
References
Computerized Medical Imaging and Graphics
3D Tomosynthesis Evaluation of Pixel Intensity Values of Breast Masses
1 Introduction
2 Methodology
3 Results
4 Discussion
5 Conclusion and Recommendations
6 Limitations of Study
References
Trident U-Net: An Encoder Fusion for Improved Biomedical Image Segmentation
1 Introduction
1.1 Motivation
1.2 Contribution
1.3 Organization
2 Related Work
3 Background Concepts
3.1 ResNet50
3.2 MobileNetV2
3.3 EffcicientNetB0
3.4 Evaluation Matrices
4 Proposed Model
5 Experiments and Results Analysis
5.1 Used Dataset
5.2 System
5.3 Results Analysis and Discussion
6 Conclusion
References
COVID-19 Detection Method from Chest CT Scans via the Fusion of Slice Information and Lung Segmentation
1 Introduction
2 Related Work
3 Materials and Methods
3.1 Dataset
3.2 Pre-processing Step
3.3 Classification Slices and Final Patient Prediction
4 Results and Discussion
5 Conclusion and Future Work
References
DenseNet for Breast Tumor Classification in Mammographic Images
1 Introduction
2 Materials and Methodology
2.1 Dataset
2.2 Segmentation
2.3 Feature Extraction and Classification: DenseNet Architecture
2.4 Evaluation Metrics
3 Results
3.1 Breast DenseNet
4 Discussion
5 Conclusions
References
Disease Control and Diagnosis
Analysing Large Repositories of Medical Images
1 Introduction
2 Making Sense Out of the Data
2.1 Deep Learning
2.2 Transfer Learning
2.3 Nooks and Crannies of Model Learning
3 Using Available Data Sources for Mining PACS Repositories
3.1 Analysing Individual Data Sources
3.2 Fusing Multimodal Data Sources
4 Conclusion
References
Fat Mass is Negatively Associated with Composite Indices of Femoral Neck Strength in Elderly Lebanese Subjects
1 Introduction
2 Material and Methods
2.1 Subjects and Study Design
2.2 Anthropometrics and Bone Measurements
2.3 Handgrip Measurements
2.4 Statistical Analysis
3 Results
3.1 Clinical Characteristics and Bone Variables of the Study Population
3.2 Correlations and Multiple Linear Regressions in Women
3.3 Correlations and Multiple Linear Regressions in Men
4 Discussion
5 Conclusion
References
Neuroimaging
Image Fusion to Guide Decision-Making Towards Minimally Invasive Epilepsy Treatment
1 Introduction
2 Methods
2.1 Application Database
2.2 Pre-processing
2.3 Detection Depth Electrodes
2.4 Exploration and Visualization of the Images
3 Results
3.1 Output of the Applications
4 Discussion
4.1 Limitations
4.2 Conclusions
References
Data-Driven EEG Informed Functional MRI Combined with Network Analysis Successfully Identifies the Seizure Onset Zone
1 Introduction
2 Materials and Methods
2.1 Subjects
2.2 Data Acquisition
2.3 Data Analysis
2.4 Comparison with Healthy Control Networks
3 Results
3.1 The Epileptic Independent Component
3.2 Epileptic Versus Resting State Networks
4 Discussion
4.1 Analysis Strategy
4.2 Clinical Evaluation
4.3 Limitations and Future Directions
4.4 Conclusions
References
Modern Neurophysiological Research of the Human Brain in Clinic and Psychophysiology
1 Introduction
2 Electroencephalography. Neurophysiological Basis
3 Brain Evoked Potentials
3.1 Evoked Potentials and Perception
3.2 Registration of Magnetic Fields
3.3 Systems "Brain-Computer Interface" Based on P300
4 Electrodermal Reactions. Super-Slow Physiological Processes
5 Other Methods in Clinical Neurophysiology and Applied Psychophysiology (USDG, PET-Scan, NIRs)
References
Application of Resting Brain Frontal Lobe Complexity in Depression Screening
1 Introduction
2 Materials and Methods
2.1 Datasets
2.2 EEG Preprocessing
2.3 Feature Extraction
2.4 Statistical Analysis
2.5 Classification
3 Results
3.1 Multivariate Multiscale Entropy and Complexity Attenuation Rate
3.2 Multiscale Entropy (Sample Entropy)
3.3 Traditional Relative Power Spectral Density
3.4 Correlation Between Features and Depression Scales
3.5 Classification
4 Conclusion
5 Discussion
References
Local Contrast Normalization to Improve Preprocessing in MRI of the Brain
1 Introduction
2 MRI Preprocessing
3 The Proposed Strategy
4 Experimental Evaluation
4.1 The Used Dataset
4.2 Results and Discussion
5 Conclusion
References
Morphological Characteristics Analysis of Working Memory Tracts Using BOLD-fMRI and HARDI Based Tractography in Healthy Human Brains
1 Introduction
2 Materials and Methods
2.1 HCP Database
2.2 Processing Pipeline Description
3 Results
3.1 Comparison Between Local Models
3.2 Comparison Between Subjects
4 Discussion
5 Conclusion and Perspectives
References
Pattern Recognition and Machine Learning for Biosignal Data
Analysis of Accuracy and Timing in Decision-Making Tasks
1 Introduction
2 Related Works of Human Decision Data Analysis
3 Experiments and Data Description
4 Methodology
5 Data Analysis
5.1 Age Grouping Assessment According to RT Data
5.2 Age Grouping Assessment According to Ac Data
5.3 Age Grouping Assessment According to Joint RT and Ac Data
5.4 Gender Grouping Assessment
6 Discussion and Conclusion
References
Recurrent Neural Networks and Efficiency in High-Dimensional EEG Classification
1 Introduction
2 The Datasets Used in This Work
3 Methodology
3.1 Recurrent Neural Networks and Model Optimization
3.2 Performance Measurement and Estimation
3.3 Analysis of Results
4 Experimental Results
4.1 Experimental Setup
4.2 Results
5 Conclusions and Future Work
References
Energy-Time Profiling for Machine Learning Methods to EEG Classification
1 Introduction
2 Methods Used to EEG Classification
2.1 K-Nearest Neighbors (KNN)
2.2 Support Vector Machine (SVM)
2.3 Random Forest
2.4 Naive Bayes
2.5 Convolutional Neural Network (CNN)
3 Methodology
3.1 Data Description
3.2 Implemented Workflow
4 Experimental Work
4.1 Setup Used
4.2 Results
5 Conclusions and Future Work
References
Performance Study of Ant Colony Optimization for Feature Selection in EEG Classification
1 Introduction
2 Ant Colony Optimization
2.1 Probabilistic Function
2.2 Pheromones Update Function
3 ACO for Feature Selection
3.1 Probabilistic Function Applied to FS
3.2 Pheromones Update Function Applied to FS
3.3 The Proposed ACO-FS Algorithm
4 ACO-FS Variants
4.1 Elitist
4.2 Rank-Based
5 Experimental Work
5.1 Setup and Methodology
5.2 Results
6 Conclusions and Future Work
References
Personalized Medicine
Comparison of Fusion Methodologies Using CNV and RNA-Seq for Cancer Classification: A Case Study on Non-Small-Cell Lung Cancer
1 Introduction
2 Related Work
3 Materials and Method
3.1 Data Acquisition and Models Evaluation
3.2 RNA-Seq Pre-processing
3.3 Copy Number Variation Pre-processing
3.4 Early Fusion
3.5 Intermediate Fusion
4 Results and Discussion
5 Conclusions
References
Artificial Corneal Transplantation and the Safe Recovery of Vision in the COVID-19 Pandemic
1 Introduction
2 Methodology
3 Discussion and Results
3.1 Corneal Transplantation
3.2 Impact of the Covid-19 Pandemic on Corneal Transplants
3.3 Artificial Corneal Transplantation
4 Final Considerations
5 Conclusion
References
COVID-19. Disease
PEAK: A Clever Python Tool for Exploratory, Regression, and Classification Data. A Case Study for COVID-19
1 Introduction
2 Materials and Methods
2.1 Import Parameters
2.2 Dataset Preprocessing
2.3 Exploratory Data Analysis
2.4 Correlation Analysis
2.5 Linear Regression Analysis
2.6 Classification
3 Conclusions
References
Prevalence of COVID-19 Amongst Arizona First Responders
1 Introduction
2 Methods
2.1 COVID-19 Antigen Test
2.2 Outcomes
2.3 Statistical Analysis
3 Results
4 Discussion
5 Conclusions
References
Interpretable COVID-19 Classification Leveraging Ensemble Neural Network and XAI
1 Introduction
2 Background Study
2.1 Literature Review
2.2 Algorithms and Architectures
3 Research Methodology
4 Dataset Details and Processing
4.1 Data Sample
4.2 Data Classification
4.3 Data Pre-processing
5 Implementation and Result Analysis
5.1 Individual Models
5.2 COVID-19 Analysis by Ensemble Modelling and Explainable AI Version 1 (COV19EXAI V1)
5.3 COVID-19 Analysis by Ensemble Modelling and Explainable AI Version 2 (COV19EXAI V2)
5.4 COV19EXI-v1 Vs COV19EXI-v2
5.5 Explainable Artificial Intelligence (XAI)
6 Conclusion
References
CoroPy: A Deep Learning Based Comparison Between X-Ray and CT Scan Images in Covid-19 Detection and Classification
1 Introduction
2 Methodology
2.1 Generating the Dataset (CovRecker)
2.2 Data Labeling
2.3 Our Proposed 19-Layer CNN Model (CoroPy) for Detecting Covid-19
2.4 Training Our Proposed Model
3 Experimental Results and Discussion
3.1 Evaluation Metrics
3.2 Performance of Our Proposed Model
3.3 Comparative Analysis with the Previous Models
4 Conclusion
References
Tomographic Identification and Evaluation of Pulmonary Involvement Due to SARS-CoV-2 Infection Using Artificial Intelligence and Image Segmentation Technique
1 Introduction
2 Literature Revision
2.1 AI and Medicine
2.2 Convolutional Neural Network
2.3 Characterization of COVID-19 in the Lung by Chest CT
2.4 Characterization of COVID-19 Severity in the Lung by Chest CT
3 Methodology
3.1 Data Base
3.2 Machine Learning
3.3 Learning Training
3.4 Metrics
3.5 Automatic Segmentation
3.6 Application
4 Results
5 Conclusion
References
COVID-19. General
Risk Group Determination in Case of COVID-19 Infection
1 Introduction
2 Prediction of Coronavirus Disease Severity Based on Genetic Mutations
3 Preliminary Results
4 Summary
References
COVID-19 Biomarkers Detection Using `KnowSeq' R Package
1 Introduction
2 Methods
2.1 Preprocessing
2.2 Differentially Expressed Genes Extraction
2.3 Feature Selection
2.4 Classification Model
2.5 Graphical Plots
3 Results and Discussions
4 Conclusions
References
Exit Strategy from COVID-19: Vaccination and Alternate Solution
1 Effects of Lockdown vs. Vaccination vs. Seasonality
2 Reporting of Short-Term Adverse Effects After Vaccination
3 Importance of Healthy Peer-review and Service to Humanity
4 Similarities Between Influenza and COVID-19
5 New Variants and Fast Mutation
6 Mass Vaccination and Transmission - Trial Experiments
7 Seasonality and COVID-19
8 Optimism with Alternative Pathways
References
COVID-19. Health
Effect of COVID-19 Lockdown on Adherence to the Mediterranean Diet Among Participants in a Health-Promotion Program
1 Introduction
2 Methods
2.1 Participants
2.2 Instruments
2.3 Procedure
2.4 Data Analysis
3 Results
4 Discussion
References
Memory Chains for Optimizing the Table Disposition During the COVID-19 Pandemic
1 Introduction
2 Mathematical Model for the Table Location Problem
3 MA for the TLP
4 Results
5 Conclusions
References
Protected Discharge Model for Mild to Moderate Covid Patients in a North-East Italian Hospital
1 Introduction
2 Methods
3 Technology Assessment
4 Flow-Chart
5 Preliminary Results
6 Conclusions
References
Exploring the Effects of Loneliness and Internet Addiction on Adults' Well-Being During COVID-19 Quarantine
1 Introduction
2 Literature Review
2.1 Mental Health Under COVID-19 Quarantine
2.2 Loneliness and PIU Under COVID-19 Quarantine
3 Methodology
3.1 Measures
3.2 Participants
3.3 Analysis Strategy
3.4 Results
4 Discussion
5 Conclusion and Future Work
Appendix
References
Short Papers
Application of Neurometrics to the Assessment of Attention Regulation Skills for Peak Performance in Sports: A Multi-method Neuroassessment Protocol
Abstract
1 Sport Neuroscience and Neuroscientific Devices for Athletes' Assessment
2 Assessment of Attention Traits in Sports: A Neurometric Approach
References
Electrophysiological Markers of Excessive Internet Use: Evidence from an ERP Study
Abstract
1 Introduction
2 Method and Materials
2.1 Sample
2.2 Experimental Procedure
2.3 EEG Acquisition and Analysis
3 Results: Correlational Analysis Between IAT and ERP
4 Discussion
References
A Computational Pipeline to Identify Potential SARS-CoV-2 Vaccine Targets
1 Extended Abstract
References
Neuroscientific Hyperscanning and Digital-Caregiving System for Monitoring and Prevention of Relational Deprivation in Dyad Frail People-Caregiver
Abstract
1 Frailty and Relational Deprivation: The Challenge of Remote Assessment and Monitoring
2 Evaluating the Quality of Relations in the Patient-Caregiver Dyad: The Hyperscanning Paradigm
References
Author Index

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