Detection of parathyroid abnormalities by analysis of optical microscopic images

Abstract

The study considers the detection of benign and malignant cases of parathyroid tumors by some image analysis techniques. The using of image analysis is a promising approach for distinguishing abnormalities of tumors, but it is rare with parathyroid ones; so it is chosen here with some Euclidian geometric features as a contribution in this field. The Fine Needle Aspiration (FNA) of parathyroid tumors is reliably used to reflect the importance of cytology for the preoperative detection of parathyroid abnormalities and their lesions. Two hundred cells images were taken from normal and abnormal specimens, extracting geometric features like Perimeter, Area, Infill Coefficient, Circularity, Elongation and using Minimum Distance as decision making to distinguish of these images. The combination of geometrical features and the proposed detection algorithm –Minimum Distance - gave good results with an accuracy of 95%.

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