eng Oriental Scientific Publishing Company Biomedical and Pharmacology Journal 0974-6242 2017-03-25 10 1 353 366 10.13005/bpj/1116 13448 article Anuranjeeta 1 K.K.Shukla 2 Anoop Tiwari 3 Shiru Sharma 1 School of Biomedical Engineering. Department of Computer Science and Engineering, Indian Institute of Technology, Banaras Hindu University. Department of Computer Science, Institute of Science, Banaras Hindu University Varanasi, Uttar Pradesh-221005, India. 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. https://biomedpharmajournal.org/vol10no1/classification-of-histopathological-images-of-breast-cancerous-and-non-cancerous-cells-based-on-morphological-features/ Image Processing Classification Fiji Morphological Feature Cancer Weka