Published Paper Details:

This article provides an overview of the existing literature on the processing of medical images related to thyroid cancer diagnosis. The primary objective of this survey is to serve as an introduction for those new to this field and as a reference for those seeking specific literature surveys in this area. In today's context, thyroid cancer is a frequently encountered concern due to the potential for malignancies and hyperactivity. Timely diagnosis is crucial in mitigating the increased malignancy of thyroid nodules. To address this, computer-aided detection methods and various image processing techniques are employed to effectively and efficiently classify thyroid nodules. Given the continuous growth of expert observations and the inherent uncertainties in medical knowledge, diagnostic imaging is essential to the medical industry. One often used technique for the precise and unambiguous identification and categorization of anomalies related to the thyroid gland is thyroid ultrasonography imaging. Computerized systems are invaluable tools for extracting features and classifying thyroid nodules, aiming to reduce misdiagnoses and enhance diagnostic accuracy. This paper's primary goal is to review the current approaches and strategies for the automatic classification of nodules in thyroid ultrasound images. It also includes performance metrics for nodule diagnosis in thyroid ultrasound images, emphasising the key differences between the strategies used.