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Stanford MedicineSarin Lab

Technologies

We develop and apply technologies that allow us to see, measure, and interpret signals in the skin. Our work spans big data analysis, optical imaging, optical clearing, three-dimensional tissue analysis, spatial biology, and artificial intelligence.

The DAMAE Medical deepLive optical imaging system, its screen showing a cross-sectional scan of skin.

Optical Imaging

We use high-resolution optical imaging, including optical coherence tomography, to examine living skin without removing tissue.

What it reveals: Skin structure and light scattering at near-cellular resolution.

Applications

Skin cancerNeurofibromatosis type 1

In collaboration with Yonatan Winetraub

Before-and-after photographs of a skin sample made optically transparent by optical clearing (5 mm scale).

Optical Clearing

Optical clearing technologies use refractive index manipulation to reduce light scattering in skin, allowing visualization of deeper tissue structures.

What it reveals: Structures below the usual imaging depth of standard optical methods.

Applications

Deeper non-invasive imagingOptical imaging researchLight-based therapy research

In collaboration with Guosong Hong

3D Molecular Pathology

We combine tissue staining, three-dimensional imaging, and computational reconstruction to study intact skin and tumor architecture.

What it reveals: The spatial organization of cells, structures, and molecular signals within tissue.

Applications

Skin tumorsNeurofibromasImaging-pathology comparison

In collaboration with Jonathan Liu

Multiplex fluorescence image mapping molecular signals within skin tissue.

Spatial Biology & Molecular Discovery

We use spatial transcriptomics, single-cell analysis, multiplex imaging, and molecular profiling to study how cells and biomarkers are organized within skin tissue.

What it reveals: The location and relationships of molecular and cellular signals within tissue.

Applications

Autoimmune and inflammatory diseaseSkin cancerBiomarker discovery

AI & Computational Analysis

We use artificial intelligence and quantitative image analysis to measure disease from clinical photographs, optical images, and pathology data.

What it reveals: Reproducible measurements of lesion number, disease burden, and treatment response.

Applications

Neurofibromatosis type 1Skin cancerClinical-trial endpoints

In collaboration with Olivier Gevaert

Interested in collaborating or learning more?