Isolation and two-step classification of normal white blood cells in peripheral blood smears

Abstract

Introduction:An automated system for differential white blood cell (WBC) counting based on morphology can make manual differential leukocyte counts faster and less tedious for pathologists and laboratory professionals. We present an automated system for isolation and classification of WBCs in manually prepared, Wright stained, peripheral blood smears from whole slide images (WSI).Methods:A simple, classification scheme using color information and morphology is proposed. The performance of the algorithm was evaluated by comparing our proposed method with a hematopathologist's visual classification. The isolation algorithm was applied to 1938 subimages of WBCs, 1804 of them were accurately isolated. Then, as the first step of a two-step classification process, WBCs were broadly classified into cells with segmented nuclei and cells with nonsegmented nuclei. The nucleus shape is one of the key factors in deciding how to classify WBCs. Ambiguities associated with connected nuclear lobes are resolved by detecting maximum curvature points and partitioning them using geometric rules. The second step is to define a set of features using the information from the cytoplasm and nuclear regions to classify WBCs using linear discriminant analysis. This two-step classification approach stratifies normal WBC types accurately from a whole slide image.Results:System evaluation is performed using a 10-fold cross-validation technique. Confusion matrix of the classifier is presented to evaluate the accuracy for each type of WBC detection. Experiments show that the two-step classification implemented achieves a 93.9% overall accuracy in the five subtype classification.Conclusion:Our methodology achieves a semiautomated system for the detection and classification of normal WBCs from scanned WSI. Further studies will be focused on detecting and segmenting abnormal WBCs, comparison of 20× and 40× data, and expanding the applications for bone marrow aspirates.

Scalable system for classification of white blood cells from Leishman stained blood stain images

“…The individual sensitivities of each WBC subtype, especially minorities like basophils, eosinophils, and monocytes, were found to be better than in many previous studies like that of Ramesh, et al . [7]…”

“…The threshold is calculated using the local curvature properties as proposed in. [7] Figure 4 illustrates the maximum curvature points of a nucleus in our dataset.…”

“…Earlier, Ongun et al .,[6] and Ramesh et al .,[7] had also proposed an automatic DBC system. In the scheme suggested by them, the WBCs were segmented by applying active contours or color-based segmentation.…”

Protective role of quercetin against manganese-induced injury in the liver, kidney, and lung; and hematological parameters in acute and subchronic rat models

“…Blood neutrophils and macrophages were visualized by peripheral blood smears. 58 A blood film or peripheral blood smear is a thin layer of blood smeared on a glass microscope slide and then stained in such a way as to allow the various blood cells (BCs) to be examined microscopically. Briefly, blood films were made by placing a drop of blood on one end of a slide and using a spreader slide to disperse the blood over the slide’s length.…”

Automatic Segmentation and Classification of White Blood Cells in Peripheral Blood Samples

“…proposed a method that combines color transformation and morphological operations and an accuracy of 93.1% was achieved. Then a two-step classification was applied with an overall accuracy of 93.9% [20].…”