Fourier ptychography microscopy for digital pathology

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Eadie, Fraser and Copeland, Laura and Di Caprio, Giuseppe and McConnell, Gail and Kallepalli, Akhil (2025) Fourier ptychography microscopy for digital pathology. Journal of Microscopy, 300 (2). pp. 260-285. ISSN 0022-2720 (https://doi.org/10.1111/jmi.70001)

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Abstract

Fourier ptychography microscopy (FPM) has made significant progress since its invention in 2013, thanks to its adaptable nature, high-resolution, and vast field-of-view capabilities. FPM is used in various medical applications across multiple optical wavelengths, from automated digital pathology to radiology and ultraviolet label-free imaging. This review explores the fundamental physical and computational concepts that have driven advancements in digital pathology using FPM. A crucial part of the progress has been the development of computational algorithms, which have directly contributed to the improvements in FPM. We evaluate early-stage algorithms like the Gerchberg-Saxton and highlight how phase-retrieval and deep-learning advancements have propelled FPM forward. Additionally, we discuss the impact of these algorithms on digital pathology for potential automated diagnosis, providing a comprehensive explanation of their influence on medical imaging and offering insights into future research directions.

ORCID iDs

Eadie, Fraser ORCID logoORCID: https://orcid.org/0009-0001-4117-4125, Copeland, Laura ORCID logoORCID: https://orcid.org/0009-0008-7117-3626, Di Caprio, Giuseppe ORCID logoORCID: https://orcid.org/0000-0001-5564-8064, McConnell, Gail ORCID logoORCID: https://orcid.org/0000-0002-7213-0686 and Kallepalli, Akhil ORCID logoORCID: https://orcid.org/0000-0001-8115-9379;
CORE (COnnecting REpositories)