BE 645: Artificial Intelligence (AI) and Radiomics (Summer 2025) - Lecture 08

BE 645: Artificial Intelligence (AI) and Radiomics (Summer 2025)

This eighth lecture focuses extensively on Local Binary Pattern (LBP) techniques within radiomics. It covers the procedural steps for LBP kernel creation, including specifying distance, theta, and rotation direction parameters, finding boundary coordinates, rotating based on theta, and assigning powers of two to kernel elements. It discusses various kernels for different theta values and clockwise or counterclockwise directions. The lecture also goes into LBP calculation steps such as thresholding neighboring pixel intensities, creating binary masks, and computing LBP values using weighted kernels. Additionally, it explores LBP's impact on texture features like energy, contrast, homogeneity, entropy, and correlation, highlighting how LBP simplifies textures, amplifies intensity differences, and introduces variability. Practical Python script outputs are provided for LBP matrix calculations with different parameters, emphasizing the application of these methods in analyzing 2D image data through Gray-Level Co-occurrence Matrix (GLCM) features.

Codes can be accessed using: https://github.com/HossamBalaha/BE-64...

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