DomainATM: Domain Adaptation Toolbox for Medical Data Analysis

TL;DR

DomainATM is an open-source MATLAB toolbox that simplifies and accelerates the application, visualization, and development of domain adaptation methods for medical data analysis, enhancing multi-site data integration.

Contribution

It provides a user-friendly, extensible platform with multiple algorithms for medical domain adaptation, facilitating research and development in this area.

Findings

Demonstrated effectiveness through three example experiments

Showed simplicity and flexibility in medical data adaptation

Enabled easy development and testing of custom methods

Abstract

Domain adaptation (DA) is an important technique for modern machine learning-based medical data analysis, which aims at reducing distribution differences between different medical datasets. A proper domain adaptation method can significantly enhance the statistical power by pooling data acquired from multiple sites/centers. To this end, we have developed the Domain Adaptation Toolbox for Medical data analysis (DomainATM) - an open-source software package designed for fast facilitation and easy customization of domain adaptation methods for medical data analysis. The DomainATM is implemented in MATLAB with a user-friendly graphical interface, and it consists of a collection of popular data adaptation algorithms that have been extensively applied to medical image analysis and computer vision. With DomainATM, researchers are able to facilitate fast feature-level and image-level adaptation, visualization and performance evaluation of different adaptation methods for medical data analysis. More importantly, the DomainATM enables the users to develop and test their own adaptation methods through scripting, greatly enhancing its utility and extensibility. An overview characteristic and usage of DomainATM is presented and illustrated with three example experiments, demonstrating its effectiveness, simplicity, and flexibility. The software, source code, and manual are available online.