Sparsity-based multi-height phase recovery in holographic microscopy.

Area of Science:

• Coherent imaging
• Digital holographic microscopy
• Image reconstruction

Background:

• Digital in-line holographic microscopy requires multiple holograms for high-resolution imaging of dense samples like pathology slides.
• Acquiring numerous holograms (6-8+) is necessary for robust phase recovery and coherent imaging, but reduces efficiency.
• Fewer measurements typically lead to reconstruction artifacts and degraded image quality, hindering biomedical applications.

Purpose of the Study:

• To develop a sparsity-based phase reconstruction technique to reduce the number of holographic measurements.
• To achieve efficient coherent imaging of densely connected samples with minimal impact on image quality.
• To enable faster and higher-throughput imaging for diagnostics.

Main Methods:

• Implemented a sparsity-based phase reconstruction technique in the wavelet domain.
• Reduced the number of holographic measurements by at least 2-fold.
• Quantified image quality using a structural similarity index.

Main Results:

• Achieved at least a 2-fold reduction in holographic measurements for coherent imaging.
• Demonstrated successful imaging of Papanicolaou smears and breast cancer tissue slides using only 2 holograms.
• Maintained high reconstructed image quality with minimal impact, validated by structural similarity index.

Conclusions:

• Sparsity-based multi-height phase recovery significantly reduces holographic measurement requirements.
• This method enables high-resolution, large field-of-view imaging of pathology slides using fewer holograms.
• The approach is extendable to other coherent imaging schemes, improving throughput and speed.