Introduction to ImageJ

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Related lectures (29)

Page 2 of 3

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.