Thyroid Disorder Detection and Review of Existing Thyroid Segmentation Techniques

Thyroid disease is a very common endocrine disorder worldwide. As thyroid functioning directly affects most of our organisms,fast and accurate recognition of thyroid diseases are of great importance.Four types of thyroid diseases are of main interest:Hypothyroidism, Hyperthyroidism. Hashimoto’s thyroiditis,(autoimmune thyroiditis), and thyroid cancer. Out of various different diagnostic tools available, a thyroid ultrasound examination gives a precise method for detection. Aim of this paper is to study various thyroid disorders and review different existing approaches/ techniques used in thyroid segmentation.Different stages required in thyroid disorder detection are introduced. As segmentation is one of the crucial methods for successful automated analysis and implementation, focus of this paper is on studying various existing segmentation techniques like,thresholding ,edge detection,region based, active contour, morphologyetc. Applying graph cut, neural networks, fuzzy principles are investigated. Also, problems faced in segmentation are discussed in brief.