It's designed to operate on a dataset of medical images and apply a series of specific transformations to each image. This process augments the original dataset, providing a greater variety of samples for training deep learning models.
Objective
Creating an intuitive graphic interface for the module
Parallelising the augmentation process to optimally utilise resources
Approach and Plan
Create the extension
Implement the augmentation process
Try to parallelise the process so that it takes as little time as possible on large data sets
Draft Status
Ready - team will start page creating immediately
Category
Quantification and Computation
Presenter Location
In-person
Key Investigators
Project Description
MONAI and PyTorch based medical image augmentation tool that can be integrated in Slicer. The project aims to be a low-code version of the tool: https://github.com/ciroraggio/AugmentedDataLoader.
It's designed to operate on a dataset of medical images and apply a series of specific transformations to each image. This process augments the original dataset, providing a greater variety of samples for training deep learning models.
Objective
Approach and Plan
Progress and Next Steps
Illustrations
No response
Background and References
https://github.com/ciroraggio/AugmentedDataLoader