• D.Nagadevi
• -

Skin cancer is the most common of all human cancers, with 1 million people in the U.S. diagnosed each year with some type of the disease. Melanoma accounts for only about 1% of skin cancer but causes a large majority of skin cancer deaths. So early diagnosis plays an essential role in control and cure of the disease. Different histology patterns of skin cancer are important for proper diagnosis and treatment of skin malignancies. In this paper different features like Nuclear-cytoplasm ratio, number of nuclei and pleomorphism or nuclei size variance of skin tissues are extracted and these features can be used for classifying the images weather they are malignant or normal tissues. So this system can be used to assist the pathologist to increase the efficiency of our health care system.

Skin tissues, Features extraction, Artificial neural networks, Nuclear-Cytoplasmic ratio (NCR).

"FEATURE EXTRACTION OF HISTOPATHOLOGICAL IMAGES OF SKIN TISSUES USING MORPHOLOGICAL OPERATIONS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.394-398, March-2019, Available :http://www.jetir.org/papers/JETIR1903059.pdf

"FEATURE EXTRACTION OF HISTOPATHOLOGICAL IMAGES OF SKIN TISSUES USING MORPHOLOGICAL OPERATIONS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp394-398, March-2019, Available at : http://www.jetir.org/papers/JETIR1903059.pdf