Day #196 - Structural Medical Image Analyses using Consistent Volume and Surface Image Processing

Key Summary

• 100 brain regions analysis
• Images -> Analysis -> Models

Image Processing

• Cohort < 200 Scans
• Big Data (Challenges and Opportunities)

Brain Research

• Brain
• Image Segmentation
• 200+ Feature variables extraction from the images

Abdomen

• Images - Segmentation - DL
• Develop Clinical Applications

Multi-Altlas Segmentation Framework

• State of art before DL
• Manually Label
• Apply deformation field
• Similar to Adaboost (Several Weak learners merge for stronger results with combinations)

Multi-Atlas Label Fusion

• Voting Label Fusion
• Majority Vote

4D Longitudinal Joint Label Fusion

• Segmentation and Results
• PCA to reduce dimensionality

Deep Machine Learning

• SLANT proposed
• Dataset Sources 

Probablistic Atlases

Multi-atlas CRUISE (MaCruise)
Analysis Brain Volume Vs Aging

Abdomen

• Image Processing
• MRI Data
• Segmentation of parts

• Segmentation is Classification Problem
• Spatial Invariance
• Localization

• GCN with larger Kernel

• GAN Application in computing

Image Synthesis

Classification and Landmark Detection

Key Learning's

• Image Segmentation
• Regression Analysis
• Cubic Spline Regression
• Deep Learning for Image Segmentation
• GAN Applications
• GCN - Global Convolutional Network - Paper

AI in Medical Imaging
Medical

• Different image sizes for X-Rays, CT-Scans
• Stacked up images, Scaling problems
• Understand in medical context
• Classification, Segmentation

Happy Mastering DL!!!