title: Automated microscopic image analysis for leukocytes identification: a survey.
abstract: Automatic quantification and classification of leukocytes in microscopic images are of paramount importance in the perspective of disease identification, its progress and drugs development. Extracting numerical values of leukocytes from microscopic images of blood or tissue sections represents a tricky challenge. Research efforts in quantification of these cells include normalization of images, segmentation of its nuclei and cytoplasm followed by their classification. However, there are several related problems viz., coarse background, overlapped nuclei, conversion of 3-D nuclei into 2-D nuclei etc. In this review, we have categorized, evaluated, and discussed recently developed methods for leukocyte identification. After reviewing these methods and finding their constraints, a future research perspective has been presented. Further, the challenges faced by the pathologists with respect to these problems are also discussed.
authors.affiliation: ABV-Indian Institute of Information Technology and Management, Gwalior, India. Electronic address: saraswatmukesh@gmail.com.
authors.forename: Mukesh
authors.initials: M
authors.lastname: Saraswat
authors.affiliation: ABV-Indian Institute of Information Technology and Management, Gwalior, India. Electronic address: kvarya@iiitm.ac.in.
authors.forename: K V
authors.initials: KV
authors.lastname: Arya
mesh_terms: D002467:Cell Nucleus / Q000000981:diagnostic imaging; D003593:Cytoplasm / Q000648:ultrastructure; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D007962:Leukocytes / Q000166:cytology* / Q000648:ultrastructure*; D008853:Microscopy / Q000379:methods; D014463:Ultrasonography
keywords: Classification; Feature extraction; Feature selection; Image preprocessing; Leukocytes segmentation