Lectures related to Introduction to ImageJ

Covers fostering advanced imaging through interdisciplinary collaborations and high-impact developments at EPFL.

Covers the practical analysis of X-ray tomography images using Fiji software.

Explores drone imaging analysis using Meshroom software for civil engineering applications.

Quantitative Imaging for Civil Engineers

Introduces quantitative imaging concepts for civil engineers, covering resolution, optics, image quality, and 3D measurements.

Image Processing Fundamentals

Covers the basics of image processing for microscopy, including acquiring, correcting defects, enhancing images, and extracting information.

Digital Images and Visual Perception

Covers the definition of digital images, image formation, classification by bit depth, and image analysis.

Computer Vision: Image Formation and Transformation

Provides an overview of image formation and transformation principles in computer vision.

Segmentation: Theory and Algorithms

Covers the theory and algorithms behind image segmentation, focusing on region identification and evaluation.

Shape from Shading: Recovering 3D Information from 2D Images

Covers the techniques for recovering 3D shape information from 2D images using shading models and modern deep learning approaches.

Image Processing Fundamentals

Covers scientific image processing fundamentals, software practices, and ethical considerations in image processing.

Texture Analysis: Statistical and Structural Approaches

Discusses texture analysis in images, focusing on statistical and structural properties, segmentation techniques, and machine learning applications for texture classification.

Image Processing in Frequency Space

Explores Fourier Transform, frequency filtering, segmentation, and particle size estimation using image analysis techniques.

Digital Images and Visual Perception

Covers the basics of digital images, image processing, and visual perception.

Image Classification: Decision Trees & Random Forests

Explores image classification using decision trees and random forests to reduce variance and improve model robustness.

Results Tables: Managing and Saving Data

Covers setting measurements, managing results, using macro language functions, getting statistics, and saving results as CSV files.

Gaussian Mixture Models: Data Classification

Explores denoising signals with Gaussian mixture models and EM algorithm, EMG signal analysis, and image segmentation using Markovian models.

Image Processing I

Covers the basics of image processing and its applications in various fields.

Batch Processing: Folder & Macro

Covers batch processing images using macros in Fiji software.

Image processing: Basics and 3D Reconstruction

Explores image processing in 2D and 3D, covering ideal imaging conditions, histogram analysis, tools, 3D reconstruction steps, and visualization.

Digital Images and Visual Perception

Emphasizes the reliability of digital image analysis over human visual perception.