# Structured Illumination Computational Microscopy with UV Surface Excitation (MUSE) for Multispectral Super-Resolution Histology

> **NIH NIH F32** · UNIVERSITY OF CALIFORNIA BERKELEY · 2020 · $23,102

## Abstract

Project Summary/Abstract
Current clinical practices for the diagnosis and management of diseases often rely on histopathological exami-
nation of tissue via optical microscopy. Brightfield imaging of hematoxylin-eosin (H&E)-stained samples repre-
sents the predominant approach for accurate and comprehensive evaluation and diagnosis in clinical histopathol-
ogy [1, 2]. Additional techniques for disease characterization involve molecularly specific labeling, and use im-
munohistochemical or immunofluorescence techniques for brightfield and fluorescence microscopy, respec-
tively. Using the latter, multiple analytes can be examined simultaneously [3, 4]. Unfortunately, the complexity of
a fluorescent microscope’s optical design scales with the number of multiplexed fluorescent reporters to visual-
ize, thus limiting its clinical utility [5]. Another area of interest is to explore clinically relevant information that may
exist at spatial resolutions beyond what can be achieved with conventional microscopes. Typical fluorescence
microscopy is generally limited by diffraction to an optical resolution of ~200 nm. Though this resolution enables
visualization of large cellular structures, it does not support examination of organelle- and suborganelle-level
ultrastructure whose morphological changes can correlate with disease, as seen in neurodegeneration, age, and
cancer [6-10]. Recently, optical super-resolution technologies have been introduced that achieve imaging reso-
lutions better than 50 nm. However, such technologies depend on complex hardware and are currently too costly
to be incorporated into typical clinical pathology budgets. Electron microscopy (EM) systems are also an availa-
ble option, and routinely image at resolutions of ~1 nm – however, these are not widely available and are not
well suited for molecular specific imaging [11-14]. Additional issues, including size, cost, limited field-of-view,
and complexity of sample-prep protocols have prevented EM from being incorporated into standard clinical work-
flow. This project will develop a robust, comparatively simple, and low-cost optical system for molecularly-specific
multispectral fluorescence imaging at spatial resolutions of ~70 nm, well beneath the classical 200 nm optical
resolution limit. To do so, a framework for computational structured illumination (SI) microscopy will be developed
to enable super-resolution using uncalibrated illumination patterns. This framework will be deployed using single-
wavelength ultraviolet (UV) excitation, which has demonstrated capabilities for simultaneous excitation of multi-
ple fluorescent reporters. Specific innovations in this work include a novel reformulation of SI microscopy that
uses computational optimization to robustly increase imaging resolution in the presence of system unknowns
and imperfections. Furthermore, because UV-based excitation has wavelengths more than a factor of 2 shorter
than the fluorophores’ visible emission wavelength...

## Key facts

- **NIH application ID:** 10213544
- **Project number:** 3F32GM129966-02S1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA BERKELEY
- **Principal Investigator:** Shwetadwip Chowdhury
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $23,102
- **Award type:** 3
- **Project period:** 2018-09-01 → 2020-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10213544

## Citation

> US National Institutes of Health, RePORTER application 10213544, Structured Illumination Computational Microscopy with UV Surface Excitation (MUSE) for Multispectral Super-Resolution Histology (3F32GM129966-02S1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10213544. Licensed CC0.

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