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J Clin Lab Anal. 2018 Jan;32(1). doi: 10.1002/jcla.22175. Epub 2017 Feb 21.

Quantitative distinction of the morphological characteristic of erythrocyte precursor cells with texture analysis using gray level co-occurrence matrix.

Author information

1
Graduate School of Health Sciences, Hokkaido University, Kita-ku, Sapporo, Japan.
2
Department of Clinical Laboratory, KKR Sapporo Medical Center, Toyohira-ku, Sapporo, Japan.
3
Department of Clinical Laboratory, Japanese Red Cross Hokkaido Block Blood Center, Nishi-ku, Sapporo, Japan.
4
Department of Health Sciences, School of Medicine, Hokkaido University, Kita-ku, Sapporo, Japan.
5
Department of Medical Laboratory Science, Faculty of Health Sciences, Hokkaido University, Kita-ku, Sapporo, Japan.
6
Department of Clinical Laboratory, Hakodate Municipal Hospital, Hakodate, Japan.
7
Department of Cardiovascular Regenerative Medicine, Osaka University Graduate School of Medicine, Suita, Japan.
8
Department of Hematology and Oncology, Hakodate Municipal Hospital, Minato-cho, Hakodate, Japan.

Abstract

BACKGROUND:

Morphological characteristics of blood cells are still qualitatively defined. So a texture analysis (Tx) method using gray level co-occurrence matrices (GLCMs; CM-Tx method) was applied to images of erythrocyte precursor cells (EPCs) for quantitatively distinguishing four types of EPC stages: proerythroblast, basophilic erythroblast, polychromatic erythroblast, and orthochromatic erythroblast.

METHODS:

Fifty-five images of four types of EPCs were downloaded from an atlas uploaded by the Blood Cell Morphology Standardization Subcommittee (BCMSS) of the Japanese Society of Laboratory Hematology (JSLH). Using in-house programs, two types of GLCMs-(R: d=1, θ=0°) and (U: d=1, θ=270°)-and nine types of texture distinction index (TDI) were calculated with images removed outer part of cell.

RESULTS:

Three binary decision trees were sequentially divided among four types of EPC with the sum average of GLCM (U), the contrast of GLCM (R), and the sum average of GLCM (U). The average concordance rate (sensitivity) of CM-Tx method with the judgments of eleven experts in the BCMSS of the JSLH was 95.8% (87.5-100.0), and the average specificity was 97.6% (92.5-100.0).

CONCLUSIONS:

The CM-Tx method is an effective tool for quantitative distinction of EPC with their morphological features.

KEYWORDS:

automatic cell classification; bone marrow; digital image processing; morphological analysis

PMID:
28220972
DOI:
10.1002/jcla.22175
[Indexed for MEDLINE]

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