Optical mesoscopy, machine learning, and computational microscopy enable high information content diagnostic imaging of blood films.

The Journal of Pathology
Michael ShawDelmiro Fernandez-Reyes

Abstract

Automated image-based assessment of blood films has tremendous potential to support clinical haematology within overstretched healthcare systems. To achieve this, efficient and reliable digital capture of the rich diagnostic information contained within a blood film is a critical first step. However, this is often challenging, and in many cases entirely unfeasible, with the microscopes typically used in haematology due to the fundamental trade-off between magnification and spatial resolution. To address this, we investigated three state-of-the-art approaches to microscopic imaging of blood films which leverage recent advances in optical and computational imaging and analysis to increase the information capture capacity of the optical microscope: optical mesoscopy, which uses a giant microscope objective (Mesolens) to enable high-resolution imaging at low magnification; Fourier ptychographic microscopy, a computational imaging method which relies on oblique illumination with a series of LEDs to capture high-resolution information; and deep neural networks which can be trained to increase the quality of low magnification, low resolution images. We compare and contrast the performance of these techniques for blood film imaging for...Continue Reading

References

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Jul 25, 2017·Optica·Roarke HorstmeyerChanghuei Yang
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Feb 6, 2020·Biomedical Optics Express·Remy ClaveauDelmiro Fernandez-Reyes
Apr 14, 2020·American Journal of Hematology·Petru ManescuDelmiro Fernandez-Reyes
Jun 6, 2020·Biomedical Optics Express·Joel T CollinsRichard Bowman

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