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Related Experiment Video

Updated: Oct 25, 2025

Guidelines and Experience Using Imaging Biomarker Explorer IBEX for Radiomics
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Radiomics software for breast imaging optimization and simulation studies.

Stoyko Marinov1, Ivan Buliev2, Lesley Cockmartin3

  • 1Medical Physics and Quality Assessment, Department of Imaging and Pathology, KU Leuven, Herestraat 49, 3000 Leuven, Belgium.

Physica Medica : PM : an International Journal Devoted to the Applications of Physics to Medicine and Biology : Official Journal of the Italian Association of Biomedical Physics (AIFB)
|August 7, 2021
PubMed
Summary
This summary is machine-generated.

A new software tool was developed for quantitative radiomics analysis in breast imaging. This tool aids in assessing image textures for optimizing new x-ray breast imaging techniques.

Keywords:
Breast imagesEvaluation of x-ray imagesFractal dimensionMatrix analysesPower law analysisStatistical features

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Area of Science:

  • Medical Imaging
  • Radiomics
  • Image Analysis

Background:

  • Quantitative assessment of image textures is crucial for developing new x-ray breast imaging modalities.
  • Current methods may benefit from optimized software for texture analysis.

Purpose of the Study:

  • To develop a software tool for routine radiomics applications in breast imaging.
  • To provide a versatile tool for quantitative image texture assessment.

Main Methods:

  • The tool was developed in MATLAB, featuring image reading, Region of Interest (ROI) selection, and analysis capabilities.
  • It includes a library of common algorithms and a user-friendly graphical interface, supporting both medical and simulated images.
  • Feature selection was based on a literature search, with the tool designed for extensibility.

Main Results:

  • The software enables semi-automatic ROI extraction and calculates 23 different metrics for 2D and 3D images.
  • Feature computations were validated against other software packages using test images.
  • Case studies demonstrated its use in comparing mammograms and evaluating breast phantom suitability.

Conclusions:

  • A novel image analysis toolbox for radiomics has been created.
  • The tool is applicable to both clinical and test images in breast imaging research.
  • It supports the optimization and development of new breast imaging technologies.