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Updated: Jul 4, 2025

Guidelines and Experience Using Imaging Biomarker Explorer IBEX for Radiomics
Published on: January 8, 2018
Imaging Genomics and Multiomics: A Guide for Beginners Starting Radiomics-Based Research
Shiva Singh1, Bahram Mohajer2, Shane A Wells3
1Radiology and Imaging Sciences, National Institutes of Health, Bethesda, Maryland.
Radiomics, the analysis of medical images for hidden data, aids in tumor detection and prognosis prediction. This guide clarifies radiomics workflows and research expectations for improved medical care.
Area of Science:
- Radiology
- Medical Imaging
- Computational Biology
Background:
- Radiomics extracts quantitative features from medical images using advanced algorithms.
- It aims to identify imaging biomarkers for improved tumor detection, prognosis, and treatment response assessment.
- Radiogenomics links imaging features with gene expression profiles, offering deeper biological insights.
Purpose of the Study:
- To describe the radiomics workflow.
- To provide guidance for initiating radiomics-based research projects.
- To address the lack of consensus on optimal radiomics methodologies.
Main Methods:
- Utilizes advanced mathematical analysis of pixel-level image data.
- Extracts quantitative features beyond traditional imaging interpretation.
- Integrates radiomics with genomics in the emerging field of radiogenomics.
Main Results:
- Radiomics enhances medical imaging by providing data for diagnosis, disease management, and prognostication.
- Identified imaging biomarkers can predict patient prognosis and treatment response.
- Radiogenomics research is expanding, investigating correlations between imaging phenotypes and genotypes.
Conclusions:
- Radiomics offers a powerful approach to leverage complex image data for clinical decision-making.
- Standardization of radiomics methods is needed to ensure reliable and reproducible research.
- Further research in radiomics and radiogenomics promises to advance precision medicine.
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