Deep Learning-Based Detection of Thyroid Nodules

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Author(s): Avani K. V. H. (BMS College of Engineering, India), Deeksha Manjunath (BMS College of Engineering, India)and C. Gururaj (BMS College of Engineering, India)
Copyright: 2023
Pages: 29
Source title: Multidisciplinary Applications of Deep Learning-Based Artificial Emotional Intelligence
Source Author(s)/Editor(s): Chiranji Lal Chowdhary (Vellore Institute of Technology, India)
DOI: 10.4018/978-1-6684-5673-6.ch008

Keywords: Artificial Intelligence / Computer Science & IT / Information Science Reference

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Abstract

Thyroid nodule is a common disease on a global scale. It is characterized by an abnormal growth of the thyroid tissue. Thyroid nodules are divided into two types: benign and malignant. To ensure effective clinical care, an accurate identification of thyroid nodules is required. One of the most used imaging techniques for assessing and evaluating thyroid nodules is ultrasound. It performs well when it comes to distinguishing between benign and malignant thyroid nodules. But ultrasound diagnosis is not simple and is highly dependent on radiologist experience. Radiologists sometimes may not notice minor elements of an ultrasound image leading to an incorrect diagnosis. After performing a comparative study of several deep learning-based models implemented with different classification algorithms on an open-source data set, it has been found that ResNet101v2 gave the best accuracy (~96%), F1 score (0.957), sensitivity (0.917), etc. A simple and easy-to-use graphical user interface (GUI) has also been implemented.

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Deep Learning-Based Detection of Thyroid Nodules

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