Paul Jaeger's repositories
prostate_segmentation
This project was carried out as part of the recruitment processs for a major AI company. The task was to implement a model for CG and PZ Prostate segementation on T2-weighted MR images. Project time were 7 days.
probabilistic_unet
A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.
batchgenerators
A framework for data augmentation for 2D and 3D image classification and segmentation
MONAI
AI Toolkit for Healthcare Imaging
kaapana
Kaapana (from the hawaiian word kaʻāpana, meaning “distributor” or “part”) is an open source toolkit for state of the art platform provisioning in the field of medical data analysis. The applications comprise AI-based workflows and federated learning scenarios with a focus on radiological and radiotherapeutic imaging.