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Recognition and classification of red blood cells using digital holographic microscopy and data clustering with discriminant analysis

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K-means clustering

k-means clustering is a method of vector quantization, originally from signal processing, that aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean (cluster centers or cluster centroid), serving as a prototype of the cluster. This results in a partitioning of the data space into Voronoi cells. k-means clustering minimizes within-cluster variances (squared Euclidean distances), but not regular Euclidean distances, which would be the more difficult Weber problem: the mean optimizes squared errors, whereas only the geometric median minimizes Euclidean distances.

Cluster analysis

Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters). It is a main task of exploratory data analysis, and a common technique for statistical data analysis, used in many fields, including pattern recognition, , information retrieval, bioinformatics, data compression, computer graphics and machine learning.

Red blood cell

Red blood cells (RBCs), also referred to as red cells, red blood corpuscles (in humans or other animals not having nucleus in red blood cells), haematids, erythroid cells or erythrocytes (from Greek erythros 'red' and kytos 'hollow vessel', with -cyte translated as 'cell' in modern usage), are the most common type of blood cell and the vertebrate's principal means of delivering oxygen (O2) to the body tissues—via blood flow through the circulatory system.

Erythrocyte deformability

Erythrocyte deformability refers to the ability of erythrocytes (red blood cells, RBC) to change shape under a given level of applied stress, without hemolysing (rupturing). This is an important property because erythrocytes must change their shape extensively under the influence of mechanical forces in fluid flow or while passing through microcirculation. The extent and geometry of this shape change can be affected by the mechanical properties of the erythrocytes, the magnitude of the applied forces, and the orientation of erythrocytes with the applied forces.

Packed red blood cells

Packed red blood cells, also known as packed cells, are red blood cells that have been separated for blood transfusion. The packed cells are typically used in anemia that is either causing symptoms or when the hemoglobin is less than usually 70–80 g/L (7–8 g/dL). In adults, one unit brings up hemoglobin levels by about 10 g/L (1 g/dL). Repeated transfusions may be required in people receiving cancer chemotherapy or who have hemoglobin disorders. Cross-matching is typically required before the blood is given.

Hierarchical clustering

In data mining and statistics, hierarchical clustering (also called hierarchical cluster analysis or HCA) is a method of cluster analysis that seeks to build a hierarchy of clusters. Strategies for hierarchical clustering generally fall into two categories: Agglomerative: This is a "bottom-up" approach: Each observation starts in its own cluster, and pairs of clusters are merged as one moves up the hierarchy. Divisive: This is a "top-down" approach: All observations start in one cluster, and splits are performed recursively as one moves down the hierarchy.

Biclustering

Biclustering, block clustering, Co-clustering or two-mode clustering is a data mining technique which allows simultaneous clustering of the rows and columns of a matrix. The term was first introduced by Boris Mirkin to name a technique introduced many years earlier, in 1972, by John A. Hartigan. Given a set of samples represented by an -dimensional feature vector, the entire dataset can be represented as rows in columns (i.e., an matrix). The Biclustering algorithm generates Biclusters.

Blood bank

A blood bank is a center where blood gathered as a result of blood donation is stored and preserved for later use in blood transfusion. The term "blood bank" typically refers to a department of a hospital usually within a Clinical Pathology laboratory where the storage of blood product occurs and where pre-transfusion and Blood compatibility testing is performed. However, it sometimes refers to a collection center, and some hospitals also perform collection.

Erythrocyte fragility

Erythrocyte fragility refers to the propensity of erythrocytes (red blood cells, RBC) to hemolyse (rupture) under stress. It can be thought of as the degree or proportion of hemolysis that occurs when a sample of red blood cells are subjected to stress (typically physical stress, and most commonly osmotic and/or mechanical stress). Depending on the application as well as the kind of fragility involved, the amount of stress applied and/or the significance of the resultant hemolysis may vary.

Determining the number of clusters in a data set

Determining the number of clusters in a data set, a quantity often labelled k as in the k-means algorithm, is a frequent problem in data clustering, and is a distinct issue from the process of actually solving the clustering problem. For a certain class of clustering algorithms (in particular k-means, k-medoids and expectation–maximization algorithm), there is a parameter commonly referred to as k that specifies the number of clusters to detect.