With the HSA Curses, HS Analysis provides specialized training for engineers and medical professionals to learn artificial intelligence in image processing with a focus on deep learning applications. Engineers and Doctors can learn to collaborate with HSA KIT for an interactive, efficient learning experience. Upon curse completion, participants will receive certification in deep learning implementation skills.
Course options include:
- Artificial Intelligence
- Deep Learning
- Classification, Object Detection, Segmentation and Instance Segmentation
- Hyperparameter Optimization
- Metrics for Deep Learning Models
- Image Analysis of Medical Data
Hybrid workshop on implementing custom deep learning models for image processing
14 December - 15 December
With the HSA Workshops, HS Analysis provides specialized training for engineers and medical professionals to learn artificial intelligence in image processing with a focus on deep learning applications. Engineers and Doctors can learn to collaborate with HSA KIT for an interactive, efficient learning experience. Upon workshop completion, participants will receive certification in deep learning implementation skills.
Course options include:
- Artificial Intelligence
- Deep Learning
- Classification, Object Detection, Segmentation and Instance Segmentation
- Hyperparameter Optimization
- Metrics for Deep Learning Models
- Image Analysis of Medical Data
Day 1
Duration: 4 hours
- Introduction
- Basics of medical imaging, AI, ML, DL and DL technologies
- Types of GTD for single deep learning technologies
- Protocols for creating GTD (HSA GTD Protocol)
- Required minimal amount and quality of GTD
- Introduction to the HSA KIT module Annotator
- Practical work and creation of GTD with HSA KIT
- Introduction to hyperparameters with HSA KIT for:
- Classification
- Object Detection
- Segmentation
- Instance Segmentation
- Practical work and training of deep learning models with HSA KIT for
- Classification
- Object Detection
- Segmentation
- Instance Segmentation
- Summary
- Discussion
Day 2
Duration: 4 hours
- Validation process theory
- Basics of metrics
- Basics of metrics for each deep learning category
- Interpretation of metrics
- Decision for the best deep learning model based on metrics
- Decision for the best deep learning model based on visual results
- Practical work on all trained deep learning models and decision for the best model for each deep learning technology
- Automated image analysis with HSA KIT
- Module selection
- Project creation
- Use of deep learning models
- Settings for deep learning models
- Processing of big data
- Quantification results
- Archiving
- Reuse of existing projects
- Foundation of objective, reproducible, and sustainable image analysis on medical images
- Summary
- Discussion