Classification of Histopathological Images of Breast Cancerous and Non Cancerous Cells based on Morphological Features

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 tiss...

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Bibliographic Details
Published in:Biomedical & pharmacology journal 2017, Vol.10 (1), p.353-366
Main Authors: Anuranjeeta, Anuranjeeta, K. Shukla, K., Tiwari, Anoop, Sharma, Shiru
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
Automation
Breast cancer
Cancer
Cell size
Classification
Datasets
Diagnosis
Histopathology
Human error
International conferences
Methods
Microscopy
Morphology
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Summary: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.
ISSN:0974-6242
2456-2610
DOI:10.13005/bpj/1116