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Ultrasonography of ovarian masses using a pattern recognition approach

As a primary imaging modality, ultrasonography (US) can provide diagnostic information for evaluating ovarian masses. Using a pattern recognition approach through gray-scale transvaginal US, ovarian masses can be diagnosed with high specificity and sensitivity. Doppler US may allow ovarian masses to...

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Autor principal: Jung, Sung Il
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society of Ultrasound in Medicine 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4484293/
https://www.ncbi.nlm.nih.gov/pubmed/25797108
http://dx.doi.org/10.14366/usg.15003
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author Jung, Sung Il
author_facet Jung, Sung Il
author_sort Jung, Sung Il
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description As a primary imaging modality, ultrasonography (US) can provide diagnostic information for evaluating ovarian masses. Using a pattern recognition approach through gray-scale transvaginal US, ovarian masses can be diagnosed with high specificity and sensitivity. Doppler US may allow ovarian masses to be diagnosed as benign or malignant with even greater confidence. In order to differentiate benign and malignant ovarian masses, it is necessary to categorize ovarian masses into unilocular cyst, unilocular solid cyst, multilocular cyst, multilocular solid cyst, and solid tumor, and then to detect typical US features that demonstrate malignancy based on pattern recognition approach.
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spelling pubmed-44842932015-07-01 Ultrasonography of ovarian masses using a pattern recognition approach Jung, Sung Il Ultrasonography Review Article As a primary imaging modality, ultrasonography (US) can provide diagnostic information for evaluating ovarian masses. Using a pattern recognition approach through gray-scale transvaginal US, ovarian masses can be diagnosed with high specificity and sensitivity. Doppler US may allow ovarian masses to be diagnosed as benign or malignant with even greater confidence. In order to differentiate benign and malignant ovarian masses, it is necessary to categorize ovarian masses into unilocular cyst, unilocular solid cyst, multilocular cyst, multilocular solid cyst, and solid tumor, and then to detect typical US features that demonstrate malignancy based on pattern recognition approach. Korean Society of Ultrasound in Medicine 2015-07 2015-02-07 /pmc/articles/PMC4484293/ /pubmed/25797108 http://dx.doi.org/10.14366/usg.15003 Text en Copyright © 2015 Korean Society of Ultrasound in Medicine (KSUM) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review Article
Jung, Sung Il
Ultrasonography of ovarian masses using a pattern recognition approach
title Ultrasonography of ovarian masses using a pattern recognition approach
title_full Ultrasonography of ovarian masses using a pattern recognition approach
title_fullStr Ultrasonography of ovarian masses using a pattern recognition approach
title_full_unstemmed Ultrasonography of ovarian masses using a pattern recognition approach
title_short Ultrasonography of ovarian masses using a pattern recognition approach
title_sort ultrasonography of ovarian masses using a pattern recognition approach
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4484293/
https://www.ncbi.nlm.nih.gov/pubmed/25797108
http://dx.doi.org/10.14366/usg.15003
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