Week 1: Digital Images
Introduction to digital image formation and how optical systems go from objects to images.
Week 2: Colors
Review of human visual perception and the RGB color model. Introduction to the concepts of image bit-depth and lookup tables.
Week3: Operating on Images
Introduction to image scaling, interpolation, and mathematical operations of images, and why certain bit-depths are more suitable than others.
Using image filtering to enhance or suppress features in an image for easing subsequent analysis. We cover linear, nonlinear and Fourier filtering with emphasis on examples.
Week 5: Image Segmentation
Introduction to image segmentation and overview of available methods (thresholding, clustering, machine learning) and morphological operations.
Week 6: Regions of Interest
Going from analyzed objects to regions of interest and results tables. Emphasis is made on how to best obtain unbiased measurements and produce a reusable image analysis workflows
Week 7: Colors, and dimensionality reduction
Introduction to color models, and color deconvolution. Overview of the concept of dimensionality reduction through image projections and reslicing and application to measuring moving objects.
Extra Week: ImageJ Macro Programming Prime
Presentation of basic programming principles applied to the ImageJ Macro Language. Crash course on variables arrays, loops, conditionals, available macro functions and writing custom functions.