ISSN: 2476-2253

Journal of Cancer Diagnosis
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  • Review Article   
  • J Cancer Diagn,
  • DOI: 10.4172/2476-2253.1000183

Review of Thyroid Cancer Diagnosis

Edwin Kaplan*
Department of Thyroid and Breast Surgery, Hebei General Hospital Affiliated to Hebei Medicine University, Shijiazhuang 050051, Hebei Province, China
*Corresponding Author : Edwin Kaplan, Department of Thyroid and Breast Surgery, Hebei General Hospital Affiliated to Hebei Medicine University, Shijiazhuang 050051, Hebei Province, China, Email: Kaplan1833010@163.com

Received Date: May 01, 2023 / Published Date: May 29, 2023

Abstract

One of the prevalent, life-threatening disorders that have been on the rise in recent years is thyroid nodule. A frequent diagnostic technique for locating and identifying thyroid nodules is ultrasound imaging. Yet, it takes time and presents difficulties for the professionals to evaluate all of the slide photos. Automated, dependable, and objective methods are required for accurately evaluating ultrasound pictures. Recent developments in deep learning have completely changed several facets of image analysis and computer-aided diagnostic (CAD) programmes that deal with the issue of identifying thyroid nodules. We reviewed the literature on the potential, constraints, and present applications of deep learning in thyroid cancer imaging and discussed the study’s goals.

Citation: Kaplan E (2023) Review of Thyroid Cancer Diagnosis. J Cancer Diagn 7: 183. Doi: 10.4172/2476-2253.1000183

Copyright: © 2023 Kaplan E. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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