Thyroid Nodules Classification in Medical Ultrasound Images using Deep Learning

  • Gulame* M
  • et al.
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Abstract

Ultrasound scanning is most excellent significant diagnosis techniques utilized for thyroid nodules identification. A thyroid nodule is unnecessary cells that can develop in your base of neck which can be normal or cancerous. Many Computer added diagnosis systems (CAD) have been developed as a second opinion for radiologist. The thyroid nodules classification using machine learning and deep learning approach is latest trend which is using to improve accuracy for differentiation of thyroid nodules from benign and malignant type. In this paper we review the most recent work on CAD system which uses different feature extraction technique and classifier used for thyroid nodules classification with deep learning approach. This paper we illustrate the result obtained by these studies and highlight the limitation of each proposed methods. Moreover we summarize convolution neural network (CNN) architecture for classification of thyroid nodule. This literature review is meant at researcher but it also useful for radiologist who is interesting in CAD tool in ultrasound imaging for second opinion.

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Gulame*, M., & Dixit, Dr. Vaibhav. V. (2020). Thyroid Nodules Classification in Medical Ultrasound Images using Deep Learning. International Journal of Innovative Technology and Exploring Engineering, 9(7), 1211–1215. https://doi.org/10.35940/ijitee.g5163.059720

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