Scalable Cytometry Image Processing (SCIP) is an open-source tool that implements an image processing pipeline on top of Dask, a distributed computing framework written in Python. SCIP performs projection, illumination correction, image segmentation and masking, and feature extraction.
After loading and fusing, we end up with a bag of (C, X, Y) tiles where every tile contains many cells. We have to identify these cells to profile them. This means we have to map a bag with m (= number of tiles) entries to a bag of n (= number of cells) entries.
This mapping could be achieved as follows:
Array of tiles (one tile = one chunk) -(to_delayed)-> array of Delayed objects of tiles -(segment)-> array of Bags of cells -(concat)-> Bag of cells
MaximLippeveld
commented
2 years ago
After loading and fusing, we end up with a bag of (C, X, Y) tiles where every tile contains many cells. We have to identify these cells to profile them. This means we have to map a bag with m (= number of tiles) entries to a bag of n (= number of cells) entries.
This mapping could be achieved as follows: Array of tiles (one tile = one chunk) -(to_delayed)-> array of Delayed objects of tiles -(segment)-> array of Bags of cells -(concat)-> Bag of cells