AI methods have become a success story and are now part of daily experience. They have also been applied in many domains of biomedical research. However, the setup and use of AI toolkits is a task requiring a lot of methodological insight as well as specialized IT expertise.
The aim of PAI is to drastically lower the entry barrier to the AI methodology for researchers analyzing biomedical images. PAI is designed as a framework, which allows users to develop their tailored AI-based image analysis solution leveraging their own training data while fully working within the familiar PMOD environment.
- PAI drastically lowers the entry barrier to AI-based image analysis.
- Using PAI, segmentation tasks can be automated based on sufficiently large sets of segmentation examples.
- Distribution includes various types of segmentation examples using different neural network architectures.
- Additionally, image classification is supported using SVM and neural network approaches.
- Users develop the solutions working fully in PMOD.
