Abstract
An outstanding challenge for immunology is the classification of immune cells in a label-free fashion with high speed. For this purpose, optical techniques such as Raman spectroscopy or digital holographic microscopy have been used successfully to identify immune cell subsets. To achieve high accuracy, these techniques require a post-processing step using linear methods of multivariate processing, such as principal component analysis. Here we demonstrate for the first time a comparison between artificial neural networks and principal component analysis (PCA) to classify the key granulocyte cell lineages of neutrophils and eosinophils using both digital holographic microscopy and Raman spectroscopy. Artificial neural networks can offer advantages in terms of classification accuracy and speed over a PCA approach. We conclude that digital holographic microscopy with convolutional neural networks based analysis provides a route to a robust, stand-alone and high-throughput hemogram with a classification accuracy of 91.3 % at a throughput rate of greater than 100 cells per second.
Highlights
Human white blood cells, which originate from haematopoietic stem cells in the bone marrow, provide protection from a wide variety of potential pathogens
Leucocytes can be further divided into granulocytes, monocytes and lymphocytes, each with individual functions, but which often act in a co-ordinated manner to combat infection
We show that digital holographic microscopy (DHM) combined with a convolutional neural network can be used as a robust, high-throughput and stand-alone hemogram for the classification of these immune cells
Summary
Human white blood cells (leucocytes), which originate from haematopoietic stem cells in the bone marrow, provide protection from a wide variety of potential pathogens. Leucocytes can be further divided into granulocytes (neutrophils, eosinophils and basophils), monocytes and lymphocytes, each with individual functions, but which often act in a co-ordinated manner to combat infection. Granulocytes, having prominent cytoplasmic granules, contain reactive enzymes which kill microbes and influence inflammation [1]. The most abundant type of granulocytes, numbering between 50 % and 70 % of circulating leucocytes under normal conditions are neutrophils which specialize in engulfing, capturing and killing microbes and bacteria like Staphylococus aureus [2]. Neutrophils have numerous immunomodulatory functions [3], including those in sepsis [4] and pattern recognition receptor functionality [5]. Defects in neutrophil granulocyte function can result in reduced resistance to infection [6], and chemotherapy-induced neutropenia is a common side-effect in patients undergoing breast cancer therapy [7]
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