DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Electronics and Computer Science-IJAECS |
 Journal Home Volume Issue |
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Issue |
Volume-10,Issue-6 ( Jun, 2023 ) | |||||||||
Paper Title |
A Review on Thyroid Nodule Segmentation | |||||||||
Author Name |
Nidhi Yadav, Priya Sharma, Sonia Verma, Astha, Najme Zehra Naqvi | |||||||||
Affilition |
1,2,3,4 Student, Computer Science and Engineering Department Indira Gandhi Delhi Technical University for Women, Delhi, India 5Assistant Professor, Computer Science and Engineering Department Indira Gandhi Delhi Technical University for Women, Delhi, India | |||||||||
Pages |
158-165 | |||||||||
Abstract |
Thyroid nodules are a frequent endocrine system problem. Thyroid nodule segmentation on ultrasound images is a crucial stage in the evaluation and identification of nodule, as well as the initial step in computer-aided diagnostic systems. Due to the poor contrast, high noise, and low resolution of ultrasound pictures, segmentation accuracy and consistency remain a difficulty. As a result, research into deep learning-based thyroid nodule segmentation algorithms is critical. This study will concentrate on the various strategies utilized for thyroid nodule segmentation. The various assessment criteria and datasets used in thyroid nodule segmentation will be discussed. This review is meant to provide readers a basic grasp of the subject. Therefore, the study of deep learning-based thyroid nodule segmentation algorithms is important. In this review, we focus on the different techniques used for thyroid nodule segmentation. We will discuss the various evaluation metrics and datasets involved in thyroid nodule segmentation. This review is intended to provide readers with a basic understanding of the topic. | |||||||||
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