Fundamentals of Bioimages

Prepared for the 2026 Taller de Fundamentos de Análisis de Bioimágenes (Formación de Formadores), this lecture lasted approximately 60 minutes. It was presented in Spanish, though the accompanying presenter notes are written in English.

The learning outcomes include:

• Digital Image Representation and Fundamentals: Quantization, intensity levels, and image formation in pixel arrays.
• Image Formation Modeling and Error Sources: Spatial uncertainty (blur via Point Spread Function or PSF), intensity noise (signal-to-noise ratio), mathematical convolution model, and Rayleigh's resolution criterion.
• Image Properties: Dimensionality (2D, 3D, wavelength, time), scale or pixel size (spatial calibration), and bit depth.
• Image Visualization: Matrix numerical value interpretation, channel splitting, orthogonal stack views, 3D/4D visualization, and Look-Up Tables (LUT).
• File Formats and Metadata: Role of metadata in experimental context, general vs. proprietary file formats (TIFF, PNG, OME-Zarr, etc.).
• ImageJ / Fiji Software Usage: Interface structure (toolbars, menu, status bar), channel management, metadata inspection, and image properties.
• Pixel Processing and Image Adjustments: Point-by-point operations (homogeneous and non-homogeneous), brightness and contrast adjustments, and threshold.
• Regions of Interest (ROI) and Quantification: Selection tools for ROIs, using the ROI Manager, and calculating quantitative measurements.
• Image Histograms: Intensity value distribution, dynamic range evaluation (underand overexposure), cumulative histograms, and histogram equalization.
• Spatial Filtering (Linear and Non-Linear): Mask and kernel operations via convolution (box, Gaussian, and Laplacian filters), non-linear filters (median and weighted median), and border handling/padding.
• Spectral Analysis and Frequency Filtering: Fourier Transform (FFT), spatial frequency representation, and application of low-pass, high-pass, and band-pass filters