Classification of Histopathological images of Breast Cancerous and Non Cancerous Cells Based on Morphological features

Anuranjeeta1, K. K. Shukla2, Anoop Tiwari3 and Shiru Sharma1


1School of Biomedical Engineering.

2Department of Computer Science and Engineering, Indian Institute of Technology, Banaras Hindu University.

3Department of Computer Science, Institute of Science, Banaras Hindu University Varanasi, Uttar Pradesh-221005, India.

Corresponding Author E-mail: anuranjeeta.rs.bme11@itbhu.ac.in

 

Abstract: This paper presents the automated detection and classification of histopathological images of cancer cells using morphological features. The manual assessment of disease is time-consuming and varies with the perception and the level of expertise of the pathologists. The judgment is based on the tissue structures, distribution of cells in tissue and the irregularities of cell shape and size. To overcome the limitation of manual diagnosis, a computer aided diagnosis based on the morphological features has been implemented for accurate and reliable detection of cancer. A dataset of 70 histopathological images of non-cancerous and cancerous tissues are randomly selected. The proposed work aims at developing the technique that uses reliable quantitative measures for providing objective and reproducible information complementary to that of a pathologist.

Keywords: Image Processing; Classification; Fiji; Morphological; Feature; Cancer; Weka

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