Detection of Tumors in Ultra Sound Thyroid Images using Random Forest Classification Method

Abstract

The thyroid gland is important for balancing the hormones in our body for our daily routine activity. This paper detects the tumor regions in ultrasound thyroid image using feature extractions based Random Forest (RF) classification approach. In this paper, Curvelet transform is used to transform the pixels associated with spatial into the pixels associated with frequency. In this paper, Random Forest (RF) classification algorithm is used for the classification of the computed features from the thyroid image.