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 the exemplar case of Giemsa-stained peripheral blood smears. Using computational image analysis and shape-based object classification, we demonstrate their use for automated analysis of red blood cell morphology and visualization and detection of small blood-borne parasites such as the malarial parasite Plasmodium falciparum. Our results demonstrate that these new methods greatly increase the information capturing capacity of the light microscope, with transformative potential for haematology and more generally across digital pathology. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Highlights

  • Microscopic analysis of blood films is fundamental to many areas of haematology from research to clinical diagnosis [1]

  • 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

  • Optical Mesoscopy (OM) using a Mesolens A Mesolens is a giant microscope objective lens designed for digital image acquisition, which has a unique combination of low magnification (4x) and high numerical aperture (NA) (0.47) to allow sub-cellular resolution imaging of sample volumes in excess of 100 mm3 [4,7]

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Summary

Introduction

Microscopic analysis of blood films is fundamental to many areas of haematology from research to clinical diagnosis [1]. Automated assessment of digitized blood films [2,3] has potential to transform overstretched clinical services that require prompt and accurate assessment of large numbers of specimens. This need is acute in low-resource settings where human expert analysis of the blood film is the only tool available. The fundamental properties of light and practical optical engineering constraints limit the ability of a conventional light microscope to capture highresolution images with a large Field of View (FoV), making it impossible to visualize an entire blood film at high spatial resolution in a single image. In addition to the high cost of traditional, clinical grade whole slide imaging systems, many such devices are incapable of achieving the high spatial resolution often required for diagnostic image-based blood film assays

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