A Hybrid Multilayer Filtering Approach for Thyroid Nodule Segmentation on Ultrasound Images-Reference-Cited by-同舟云学术

A Hybrid Multilayer Filtering Approach for Thyroid Nodule Segmentation on Ultrasound Images

Published:2018-08-31 Issue:3 Volume:38 Page:629-640
ISSN:0278-4297
Container-title:Journal of Ultrasound in Medicine
language:en
Short-container-title:J Ultrasound Med

Author:

Abbasian Ardakani Ali¹^ORCID,Bitarafan-Rajabi Ahmad¹²,Mohammadzadeh Ali³,Mohammadi Afshin⁴^ORCID,Riazi Reza¹,Abolghasemi Jamileh⁵⁶,Homayoun Jafari Amir⁷,Bagher Shiran Mohammad¹

Affiliation:

1. Department of Medical Physics; School of Medicine, Tehran University of Medical Sciences; Tehran Iran

2. School of Medicine, Department of Nuclear Medicine; Tehran University of Medical Sciences; Tehran Iran

3. Department of Radiology; Tehran University of Medical Sciences; Tehran Iran

4. Department of Radiology, Faculty of Medicine, Imam Khomeini Hospital; Urmia University of Medical Sciences; Urmia Iran

5. Department of Rajaei Cardiovascular, Medical, and Research Center; Tehran University of Medical Sciences; Tehran Iran

6. Department of Biostatistics, School of Public Health; Tehran University of Medical Sciences; Tehran Iran

7. Department of Medical Physics & Biomedical Engineering; School of Medicine, Iran University of Medical Sciences; Tehran Iran

Funder

Iran University of Medical Sciences

Publisher

Wiley

Subject

Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/jum.14731/fullpdf

Reference20 articles.

1. 2015 American Thyroid Association management guidelines for adult patients with thyroid nodules and differentiated thyroid cancer: the American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer;Haugen;Thyroid,2016

2. US artifacts;Feldman;Radiographics,2009

3. Computer-aided diagnosis: how to move from the laboratory to the clinic;Ginneken;Radiology,2011

4. A review on ultrasound-based thyroid cancer tissue characterization and automated classification;Acharya;Technol Cancer Res Treat,2014

5. Classification of benign and malignant thyroid nodules using wavelet texture analysis of sonograms;Ardakani;J Ultrasound Med,2015

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