Machine Learning Thyroid Nodules Classification
Sruthy B.S1, S. Muruganantham2
1Sruthy B., Research Scholar, Department of Computer Science, S.T. Hindu College, Nagercoil, Affliatedto Manonmanium Sundaranar Universi ty, Tirunelveli (Tamil Nadu), India.
2Dr. S. Muruganantham, Research Scholar, Department of Computer Science, S.T. Hindu College, Nagercoil Affliatedto Manon Manium Sundaranar University, Tirunelveli (Tamil Nadu), India.
Manuscript received on 22 May 2019 | Revised Manuscript received on 08 June 2019 | Manuscript Published on 15 June 2019 | PP: 358-364 | Volume-8 Issue-1S2 May 2019 | Retrieval Number: A00840581S219/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: An overview is presented of thyroid medical image processing literature on thyroid cancer diagnosis.The main aim of this survey is to introduce for those new to this feild,and a reference for those who searching for specific literature survey on application.Thyroid cancer is now commonly seen one and main concern in nowdays due to the risk of malignancies and hyper function.The nodules becomes more malignant if it is not diagnosied at right time.computer aided detection of thyroid nodules and various image processing techniques and methods are used for effective and efficient classification of thyroid nodules. Diagnostic imaging is an important tool in medical science due to the continuous observations of the expert and uncertaninty in medical knowledge. A thyroid ultrasound is a more commonly used imaging study used to detect and classify abnormalities of the thyroid gland clearly and correctly. Computerized system is a valuable and beneficial means for feature extraction and classification of thyroid nodule in order to eliminate false diagnosis and to improve the diagnostic accuracy. The main aim of this paper is to review existing methods and techniques to the automatic classification of nodules in thyroid ultrasound images, highlighting the main differences between the used strategies and also for the diagnosis of Nodules in thyroid ultrasound images with their performance measures.
Keywords: Nodules, Thyroid, Ultrasound, Classification, Cance Rdiagnosis, Image Processing.
Scope of the Article: Machine Learning