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Texture Analysis of Abnormal Cell Images for Predicting the Continuum of Colorectal Cancer
Joint Authors
Chaddad, Ahmad
Tanougast, Camel
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-01-17
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Abnormal cell (ABC) is a markedly heterogeneous tissue area and can be categorized into three main types: benign hyperplasia (BH), carcinoma (Ca), and intraepithelial neoplasia (IN) or precursor cancerous lesion.
In this study, the goal is to determine and characterize the continuum of colorectal cancer by using a 3D-texture approach.
ABC was segmented in preprocessing step using an active contour segmentation technique.
Cell types were analyzed based on textural features extracted from the gray level cooccurrence matrices (GLCMs).
Significant texture features were selected using an analysis of variance (ANOVA) of ABC with a p value cutoff of p < 0.01 .
Features selected were reduced with a principal component analysis (PCA), which accounted for 97% of the cumulative variance from significant features.
The simulation results identified 158 significant features based on ANOVA from a total of 624 texture features extracted from GLCMs.
Performance metrics of ABC discrimination based on significant texture features showed 92.59% classification accuracy, 100% sensitivity, and 94.44% specificity.
These findings suggest that texture features extracted from GLCMs are sensitive enough to discriminate between the ABC types and offer the opportunity to predict cell characteristics of colorectal cancer.
American Psychological Association (APA)
Chaddad, Ahmad& Tanougast, Camel. 2017. Texture Analysis of Abnormal Cell Images for Predicting the Continuum of Colorectal Cancer. Analytical Cellular Pathology،Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1121732
Modern Language Association (MLA)
Chaddad, Ahmad& Tanougast, Camel. Texture Analysis of Abnormal Cell Images for Predicting the Continuum of Colorectal Cancer. Analytical Cellular Pathology No. 2017 (2017), pp.1-13.
https://search.emarefa.net/detail/BIM-1121732
American Medical Association (AMA)
Chaddad, Ahmad& Tanougast, Camel. Texture Analysis of Abnormal Cell Images for Predicting the Continuum of Colorectal Cancer. Analytical Cellular Pathology. 2017. Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1121732
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1121732