ScalableCytometryImageProcessing/SCIP
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.
PythonGPL-3.0
Issues
- 1
Is this pipeline actively maintained?
#53 opened by tatyana-perlova - 0
- 0
Use pre-commit package for enforcement
#50 opened by MaximLippeveld - 0
Add unit tests
#7 opened by MaximLippeveld - 1
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- 2
- 0
- 0
- 0
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Update masking for IFC data
#43 opened by MaximLippeveld - 0
Support for CZI images
#40 opened by MaximLippeveld - 1
Segmentation of optical microscopy images
#42 opened by MaximLippeveld - 0
- 1
Add Local Binary Pattern texture features
#24 opened by MaximLippeveld - 1
Move UMAP to separate module
#25 opened by MaximLippeveld - 0
Add per-image min-max normalization
#26 opened by MaximLippeveld - 0
- 0
Benchmark/use DoG instead of Non-local means denoising in mask segmentation
#18 opened by sanderthierens - 0
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Add demo dataset for new users
#1 opened by MaximLippeveld - 1
Export to AnnData
#37 opened by MaximLippeveld - 0
Better basic mask quality control
#38 opened by MaximLippeveld - 0
Export mask bounding box
#39 opened by MaximLippeveld - 0
Add per-sample min-max normalization
#28 opened by MaximLippeveld - 0
Render reports using Jinja template engine
#30 opened by MaximLippeveld - 0
Fix hog features
#31 opened by MaximLippeveld - 0
Add CellProfiler granularity features
#32 opened by MaximLippeveld - 1
Switch to async cluster for benchmarking
#36 opened by MaximLippeveld - 0
Implement principal feature analysis
#13 opened by MaximLippeveld - 1
Use CellProfiler to extract features
#16 opened by MaximLippeveld - 0
- 1
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Option to persist feature dataframes to disk (data format yet to be decided. Likely, SQLite and feather)
#21 opened by MaximLippeveld - 0
- 1
- 0
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Add info and debug logging statements
#10 opened by MaximLippeveld - 3
- 0
Add pipeline and run configuration
#3 opened by MaximLippeveld - 1
- 1
Image normalization after masking
#5 opened by MaximLippeveld - 0
Masking quality control report
#6 opened by MaximLippeveld - 0
Compute CP MeasureImageQuality features to filter out abberant images prior to full computation
#34 opened by MaximLippeveld - 1
Smart indexing on Dask Dataframe
#20 opened by MaximLippeveld - 0
Rewrite reporting and exporting flow
#29 opened by MaximLippeveld - 0
Crop images to bounding box of mask to reduce computation and storage overhead
#33 opened by MaximLippeveld - 3
Perform background subtraction
#11 opened by MaximLippeveld - 2
Channel normalisation
#14 opened by sanderthierens - 0