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PoL Bio-Image Analysis Training School - Early Career Track
Monday
Course preparation
Introduction to Python part I
Basic types in python
Cropping lists
Cropping images
Masking numpy arrays
Introduction to Python part II
Conditions
Functions
Loops
Image Analysis Basics
Images in python
Brightness and Contrast
Using Napari to visualize and interact with images
Reading files with AICSImageIO
Image Processing
Filters and Background Reduction
The Napari Assistant
Generating Jupyter Notebooks from the Napari Assistant
Optional: 3D Image Filters
Tuesday
Image segmentation
Exercise: Thresholding
Label images
Voronoi-Otsu-labeling
Marching cubes
Working with surfaces
Basics of vedo
Volume data in vedo
Point clouds in vedo
Build a mesh
Map data on mesh
Interpolate scalar data on mesh
Convert images to meshes
Mesh manipulation
Signed distance from mesh surface
Advanced mesh morphing
Machine learning for object segmentation
Supervised machine learning
Interactive pixel classification and object segmentation in Napari
Pixel classification using Scikit-learn
Interactive object classification in Napari
Object segmentation on OpenCL-compatible GPUs
Feature extraction
Object Size, Shape & Intensity
Sphericity & Solidity
Working with tabular data and Statistics
Essentials for Exploring and Visualizing Data with Pandas
Introduction to Pandas
Basic Operations
Exploratory Data Analysis
Basic Plots, Groupping and Multi-Level Tables
Statistics
Wednesday
Plotting Data with Python
Plotting Data with Matplotlib
Introduction to Seaborn
Using Seaborn to Plot Distributions
Adding Statistic Annotations
Bio-image Analysis Workflow Exercise
Workflow Exercise
Repository
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