Deep learning image analysis for continuous single-cell imaging of dynamic processes in Plasmodium falciparum-infected erythrocytes

The accompanying code base can be found at https://github.com/sciai-lab/CP_RBC_Pfalciparum. Please download the data, unzip it and place it in the directory data of the repository. 

 Details

parasite_labelled contains the raw data and ground truth segmentations for individual 3D stacks of ring-stage (mask-r) and trophozoite/schizont (mask-ts) parasites. rbc_labelled contains the raw data and ground truth segmentations for individual 3D stacks for the erythrocytes. The corresponding results subdirectories contain the predicted segmentations and evaluation metrics of the 10-fold cross-validation. These datasets were used for training and cross-validating the cellpose models

wholelife_unlabelled contains raw data and predicted segmentations for whole life cycle recordings (3D stacks across time).