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DomainATM: Domain adaptation toolbox for medical data analysis
1The Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Neuroimage
|January 7, 2023
Summary
Domain Adaptation Toolbox for Medical data analysis (DomainATM) is a new MATLAB package for machine learning in healthcare. It simplifies using and developing domain adaptation methods for medical data analysis.
Area of Science:
- Machine Learning
- Medical Data Analysis
- Computer Vision
Background:
- Domain adaptation (DA) is crucial for machine learning in medical data analysis.
- DA reduces distribution differences between medical datasets, enhancing statistical power by pooling multi-site data.
Purpose of the Study:
- Introduce Domain Adaptation Toolbox for Medical data analysis (DomainATM), an open-source MATLAB software package.
- Facilitate and customize domain adaptation methods for medical data analysis.
Main Methods:
- DomainATM is implemented in MATLAB with a user-friendly graphical interface.
- Includes popular data adaptation algorithms for medical image analysis and computer vision.
- Supports feature-level and image-level adaptation, visualization, and performance evaluation.
Main Results:
- Demonstrates effectiveness, simplicity, and flexibility through three example experiments.
- Enables users to develop and test their own adaptation methods via scripting.
- Software, source code, and manual are available online.
Conclusions:
- DomainATM enhances utility and extensibility for medical data analysis researchers.
- Promotes efficient application and development of domain adaptation techniques.
- Facilitates robust analysis of multi-center medical datasets.
