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Radiomics is a field that involves extracting large amounts of quantitative features from medical images using data-characterization algorithms. These features, known as radiomics features, can be used for various applications such as diagnosing diseases, predicting outcomes, or assessing response to therapy.

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SaraAghamiri/Radiomics_tutorial

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Radiomics_tutorial0

First, Click the star above for this GitHub repository! :)

Objective: The purpose of this GitHub repository is to supply a foundational educational tool for conducting radiomics research, particularly emphasizing the relationship between radiological imaging features and patient outcomes in glioblastoma cases. This repository hosts a computational framework meant to process and examine datasets comprising various radiomics parameters, such as tumor volume, texture, and intensity variations extracted from MRI images.

Background: Radiomics is a field that involves extracting large amounts of quantitative features from medical images using data-characterization algorithms. These features, known as radiomics features, can be used for various applications such as diagnosing diseases, predicting outcomes, or assessing response to therapy.

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Radiomics is a field that involves extracting large amounts of quantitative features from medical images using data-characterization algorithms. These features, known as radiomics features, can be used for various applications such as diagnosing diseases, predicting outcomes, or assessing response to therapy.

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