Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing - Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing -

Introduction Comparison Between 2D and 3D Techniques in Medical Imaging Importance of 3D Medical Image Medical Imaging Types and Modalities Computer Vision System Works in 3D Image Analysis Various Techniques in 3D Image Processing in Medical Imaging Types of Medical Imaging Compressed by 3D Medical Visualization D Ultrasound Shortens The Imaging Development Conclusion References Automated Epilepsy Seizure Detection from EEG Signals Using Deep CNN Model Introduction Materials and Methodology Dataset. Normalization Convolution Neural Network (CNN)Result and Discussions Experiment 1: 10-Fold Cross Validation on 90:10 Ratio Experiment 2: Training and Testing Ratio Variation Conclusion References Medical Image De-Noising Using Combined Bayes Shrink and Total Variation Techniques Introduction Literature Review Theoretical Analysis Total Variation Technique Pixel Level DTCWT Image Fusion Technique Performance Evaluation Parameters Methodology Results And Discussion Conclusions And Future Scope References Detection of Nodule and Lung Segmentation Using Local Gabor XOR Pattern in CT Images Introduction Histories Concepts Causes for Lung Cancer Solution Methodology With Mathematical Formulations Morphological Operation Conclusions and Future Work References Medical Image Fusion Using Adaptive Neuro Fuzzy Inference System Introduction Overview Digital Image Types of Digital Images Medical Imaging Type Image Fusion Literature Survey A Brief History about Literature Survey Solution Methodology Proposed Methodology Applying to ANFIS Result and Discussion Conclusion and Future Scope References Medical Imaging in Healthcare Applications Introduction Image Modalities PET Scan Ultrasound MRI Scan CT Scan Recent Trends in Healthcare Technology Scope for Future Work Conclusions References Classification of Diabetic Retinopathy by Applying an Ensemble of Architectures Introduction Literature Survey Method and Data Results Conclusion References Compression of Clinical Images Using Different Wavelet Function Introduction: Background and Need of Compression Terminology UtilizeD for Implementation Proposed Algorithm Calculation for Picture Compression Utilizing Wavelet Input Image Compression Decompression and Filters Compression Image Reconstruction Performance Analysis Implementation and Result Analysis of CT Scan Images Wavelet Haar Function Is Used Conclusion References PSO-Based Optimized Machine Learning Algorithms for the Prediction of Alzheimer's Disease Introduction Related Work Material and Methods Proposed Workflow Database Data Pre-processing Particle Swarm Optimization (PSO) Techniques Machine Learning Models Experimental Results Discussion Conclusion References Parkinson's Disease Detection Using Voice Measurements Introduction Literature Survey Parkinson's Syndromes Symptoms Causes Threat Causes Complications Methodologies Used in Present Work Machine Learning (ML) and Artificial Intelligence (AI)Ensemble Learning Advantages Data Drive Machine Learning Architecture Proposed System Testing Conclusion and Future Enhancements References Speech Impairment Using Hybrid Model of Machine Learning Introduction Types of Classifier Related Work Proposed Work Results and Discussions Conclusion References Advanced Ensemble Machine Learning Model for Balanced BioAssays Introduction Related Work Proposed Work Experimental Investigation Results Conclusion References Lung Segmentation and Nodule Detection in 3D Medical Images Using Convolution Neural Network Introduction Review of Literature Rationale of the Study Morphological Processing of the Digital Image Objectives of Study Proposed Methodology Expected Outcome of Research Work Conclusion and Future work References