Automated detection of working area of peripheral blood smears using mathematical morphology

68Citations
Citations of this article
41Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

The paper presents a technique to automatically detect the working area of peripheral blood smears stained with May-Grünwuald Giemsa. The optimal area is defined as the well spread part of the smear. This zone starts when the erythrocytes stop overlapping (on the body film side) and finishes when the erythrocytes start losing their clear central zone (on the feather edge side). The approach yields a quick detection of this area in images scanned under low magnifying power (immersion objective x 25 or x 16). The algorithm consists of two stages. First, an image analysis procedure using mathematical morphology is applied for extracting the erythrocytes, the centers of erythrocytes and the erythrocytes with center. Second, the number of connected components from the three kinds of particles is counted and the coefficient of spreading ρs and the coefficient of overlapping ρo are calculated. The data from fourteen smears illustrate how the technique is used and its performance. Colour figures can be viewed on http://www.esacp.org/acp/2003/25-1/angulo.htm.

References Powered by Scopus

A survey on image segmentation

976Citations
N/AReaders
Get full text

Proposals for the classification of chronic (mature) B and T lymphoid leukaemias

739Citations
N/AReaders
Get full text

An Analysis of Histogram-Based Thresholding Algorithms

564Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Automatic recognition of five types of white blood cells in peripheral blood

301Citations
N/AReaders
Get full text

Effective segmentation and classification for HCC biopsy images

133Citations
N/AReaders
Get full text

Computer vision for microscopy diagnosis of malaria

127Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Angulo, J., & Flandrin, G. (2003). Automated detection of working area of peripheral blood smears using mathematical morphology. Analytical Cellular Pathology, 25(1), 37–49. https://doi.org/10.1155/2003/642562

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 18

72%

Professor / Associate Prof. 4

16%

Researcher 3

12%

Readers' Discipline

Tooltip

Engineering 11

35%

Computer Science 10

32%

Medicine and Dentistry 7

23%

Agricultural and Biological Sciences 3

10%

Save time finding and organizing research with Mendeley

Sign up for free