Robust Structured Illumination Microscopy Data with Synthetic and Experimental Images

Experimental and synthetic image data for structured illumination microscopy (SIM) reconstruction. The collection includes fluorescence images of calibration slides and live HeLa cell mitochondria, synthetic line pair patterns, and camera calibration maps. The data was associated with a research paper by Ayush Saurabh of Arizona State University.

Use Cases

• Testing and benchmarking SIM reconstruction algorithms based on the provided Wiener and FISTA-SIM scripts.
• Developing noise control methods for microscopy using the provided synthetic line pair patterns.
• Calibrating imaging systems using the included camera calibration maps for gain, variance, and offset.
• Studying mitochondrial structures in live cells based on the MitoTracker Red labelled HeLa cell images.

Strengths

• Includes both experimental and synthetic data, allowing for controlled algorithm testing.
• Provides estimated SIM patterns necessary for the described Bayesian noise control (B-SIM) method.
• Contains camera calibration maps (gain, variance, offset), which are essential for quantitative image analysis.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.

Provenance

Source

Arizona State University (Ayush Saurabh)

Collection Method

Likely generated from microscopy experiments and computational simulations for a specific research publication.