An Approach for Automated Detection and Classification of Thyroid Cancer Cells

Cancer that forms in the thyroid gland (an organ at the base of the throat that makes hormones that help control heart rate, blood pressure, body temperature, and weight) is known as the Thyroid Cancer. The prognosis of thyroid cancer is related to the type of cancer. This approach is based on a developed computer analyzer of images that is aimed at automated processing, detection and classification of thyroid cancer cells. It also classifies the type of thyroid cancer present in the digital image of the cell. Classification, a data mining function which accurately predicts the target class for each case in the data. Template matching technique is used in order to match on pixel by pixel basis. It works by sliding the template across the original image. As it slides, it compares or matches the template to the portion of the image directly under it. By this technique the defected cells are well enhanced and the types of thyroid cancer are distinguished. Thus by depending upon the decision rule, all pixels are classified in a single class and hence the types of thyroid cancer cells are well categorized. This method enhances the cell in an efficient manner and effectively separates the cancer cells from the background. This demonstrates the potential effectiveness of the system that enables the medical practitioners to perform the diagnostic task and proper medication.