Lensless Digital Holographic Microscopy for differentiation and counting of blood cells in a microfluidic device using Computer Vision

This research paper presents lensless digital holographic microscopy (LDHM) combined with
computer vision techniques for differentiating and counting blood cells in microfluidic flow.
A lensless holographic imaging setup captures holographic interference patterns of blood cells in a
microfluidic channel using a digital sensor. LDHM eliminates the need for lenses, allowing for low
cost, simplistic and robust designs, increasing suitability for decentralised testing and personalised
healthcare. LDHM offers advantages of non-invasiveness, label-free and potential for real-time
results; by utilising computer vision, it enables rapid and automated detection of particle populations,
potentially aiding early disease detection and assessing treatment success via ongoing monitoring.
Computer vision algorithms allow for reconstruction of holograms, in order for further analysis such
as to extract features, and classify cells based on morphology. This allows for a sample to be
monitored over time, allowing for an accurate count of particles over time and averaging to generate
an accurately calculated particle concentration.
This paper aims to display the potential for LDHM for blood cell differentiation and count as a form
of blood analysis, and how this technology can be designed in an effective yet affordable manner, with
its simplistic design having further potential for point-of-care translation.