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MilxXplore: a web-based system to explore large imaging datasets
P Bourgeat1, V Dore, V L Villemagne
1CSIRO Preventative Health National Research Flagship ICTC, The Australian e-Health Research Centre, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia.
Summary
MilxXplore is an open-source platform for efficient quality control of large-scale medical imaging studies. It enables collaborative review and reporting of automated image analysis results, facilitating data sharing and open science initiatives.
Area of Science:
- Medical Imaging
- Computational Biology
- Data Science
Background:
- Large-scale medical imaging studies necessitate automated software for quantitative information extraction.
- Increasing cohort sizes demand efficient tools for quality checking, tagging, and reporting of automated image analysis results, especially for problematic cases.
Purpose of the Study:
- To introduce MilxXplore, an open-source visualization platform designed for efficient quality control and reporting in large-scale medical imaging studies.
- To provide a user-friendly, collaborative, and efficient interface for navigating and exploring imaging data and analysis results.
Main Methods:
- MilxXplore is an open-source visualization platform accessible via a web browser.
- It offers an interface for users to navigate and explore imaging data.
- The platform supports quality control and reporting functionalities.
Main Results:
- MilxXplore pools results from individual subjects and time points, enabling efficient navigation and comparison across acquisitions and populations.
- It facilitates remote quality checks of processed imaging data.
- The platform is fast, flexible, and easily integrated into cloud computing pipelines.
Conclusions:
- MilxXplore enhances the efficiency of quality control and reporting for large-scale medical imaging studies.
- It promotes data sharing and collaboration across multiple locations, supporting open data and open science trends.
- The platform is crucial for sharing and publishing imaging analysis results in the era of big data.
