Biomedical Imaging and Data Analysis
( 25 Modules )

Module #1
Introduction to Biomedical Imaging
Overview of biomedical imaging, importance, and applications

Module #2
Imaging Modalities
Introduction to different imaging modalities (X-ray, CT, MRI, Ultrasound, PET)

Module #3
Image Acquisition and Reconstruction
Principles of image acquisition and reconstruction in different modalities

Module #4
Image Processing Fundamentals
Basic concepts of image processing ( filtering, thresholding, morphology)

Module #5
Image Enhancement and Restoration
Techniques for image enhancement and restoration (noise reduction, de-blurring)

Module #6
Image Segmentation
Introduction to image segmentation techniques (thresholding, edge detection, clustering)

Module #7
Image Registration
Introduction to image registration techniques (rigid, affine, non-rigid)

Module #8
Feature Extraction and Selection
Techniques for feature extraction and selection (texture, shape, intensity)

Module #9
Classification and Clustering
Introduction to classification and clustering techniques (k-NN, SVM, k-means)

Module #10
Biomechanics and Image-Based Modeling
Introduction to biomechanics and image-based modeling

Module #11
Medical Image Analysis Applications
Applications of medical image analysis (tumor detection, cardiac imaging, neuroimaging)

Module #12
Data Preprocessing and Quality Control
Importance of data preprocessing and quality control in biomedical imaging

Module #13
Statistical Analysis in Biomedical Imaging
Introduction to statistical analysis techniques in biomedical imaging

Module #14
Machine Learning in Biomedical Imaging
Introduction to machine learning techniques in biomedical imaging (deep learning, transfer learning)

Module #15
Image-Guided Interventions
Introduction to image-guided interventions (surgery, radiation therapy)

Module #16
Image-Based Biomarkers
Introduction to image-based biomarkers and their applications

Module #17
Biomedical Image Informatics
Introduction to biomedical image informatics and its applications

Module #18
Data Visualization in Biomedical Imaging
Introduction to data visualization techniques in biomedical imaging

Module #19
Collaborative Tools and Platforms
Introduction to collaborative tools and platforms for biomedical imaging research

Module #20
Ethical and Regulatory Considerations
Ethical and regulatory considerations in biomedical imaging research

Module #21
Case Studies in Biomedical Imaging
Real-world case studies in biomedical imaging research

Module #22
Current Trends and Future Directions
Current trends and future directions in biomedical imaging research

Module #23
Hands-on Exercise:Image Analysis
Hands-on exercise in image analysis using popular software tools

Module #24
Hands-on Exercise:Machine Learning
Hands-on exercise in machine learning using popular software tools

Module #25
Course Wrap-Up & Conclusion
Planning next steps in Biomedical Imaging and Data Analysis career

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Biomedical Imaging and Data Analysis ( 25 Modules )

Biomedical Imaging and Data Analysis
( 25 Modules )