Computational 3D Resolution Enhancement for Optical Coherence Tomography

Phase-corrected and processed optical coherence tomography datasets accompany a 2023 publication in Biomedical Optics Express. Jos de Wit from Delft University of Technology provides data underlying figures, including point scatterer and leaf sample measurements. The repository contains both input and processed datasets to support replication of computational enhancement methods.

Use Cases

• Benchmarking computational adaptive optics algorithms based on the provided aberration-corrected data.
• Testing 3D resolution enhancement methods using the included phase-corrected OCT datasets of point scatterers and leaf samples.
• Reproducing figures from the associated publication by processing the supplied data with the included MATLAB and Python scripts.

Strengths

• Includes processed datasets used as the basis for figures in a peer-reviewed 2023 publication.
• Provides both phase-corrected input data and aberration-corrected output data for multiple samples.

Limitations

• Row count and dataset size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred from the publication or scripts.
• Some processed data contains random noise and apertures, so results may vary upon re-running scripts.

Provenance

Source

Delft University of Technology

Collection Method

Experimental optical coherence tomography measurements and computational processing, as described in the associated publication.