Project Computational Microscopy
BSCCM microscopy image-to-image pipeline
A reproducible image-to-image benchmark pipeline built on the BSCCM dataset. The project uses 23 label-free microscopy views to predict 6 fluorescence channels, with an emphasis on controlled data handling, explicit run configuration, and stable evaluation before broader model comparisons.
Why it matters Microscopy model comparisons are easy to distort when data handling, preprocessing, and evaluation are inconsistent. This project focuses on building a baseline that is stable enough to trust before adding more model complexity.
Current checkpoint Locking down a baseline that is actually trustworthy to compare: fixed data handling, explicit run configuration, stable metrics, and saved artifacts that make errors easier to inspect.