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

Medical image fusion is a process which merges information from multiple images of the same scene. The fused image provides appended information that can be utilized for more precise localization of abnormalities. The use of medical image processing databases will help to create and develop more accurate and diagnostic tools.

1. An Introduction to Medical Image Analysis in 3D 2. Automated Epilepsy Seizure Detection from EEG Signals Using Deep CNN Model 3. Medical Image De-Noising Using Combined Bayes Shrink and Total Variation Techniques 4. Detection of Nodule and Lung Segmentation Using Local Gabor XOR Pattern in CT Images 5. Medical Image Fusion Using Adaptive Neuro Fuzzy Inference System 6. Medical Imaging in Healthcare Applications 7. Classi¿cation of Diabetic Retinopathy by Applying an Ensemble of Architectures 8. Compression of Clinical Images Using Different Wavelet Function 9. PSO-Based Optimized Machine Learning Algorithms for the Prediction of Alzheimer's Disease 10. Parkinson's Disease Detection Using Voice Measurements 11. Speech Impairment Using Hybrid Model of Machine Learning 12. Advanced Ensemble Machine Learning Model for Balanced BioAssays 13. Lung Segmentation and Nodule Detection in 3D Medical Images Using Convolution Neural Network