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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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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Korean Society of Ultrasound in Medicine
2015
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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 |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-4484293 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Korean Society of Ultrasound in Medicine |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT jungsungil ultrasonographyofovarianmassesusingapatternrecognitionapproach |