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Interactive Outlining of Pancreatic Cancer Liver Metastases in Ultrasound Images
Ultrasound (US) is the most commonly used liver imaging modality worldwide. Due to its low cost, it is increasingly used in the follow-up of cancer patients with metastases localized in the liver. In this contribution, we present the results of an interactive segmentation approach for liver metastas...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5429849/ https://www.ncbi.nlm.nih.gov/pubmed/28420871 http://dx.doi.org/10.1038/s41598-017-00940-z |
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author | Egger, Jan Schmalstieg, Dieter Chen, Xiaojun Zoller, Wolfram G. Hann, Alexander |
author_facet | Egger, Jan Schmalstieg, Dieter Chen, Xiaojun Zoller, Wolfram G. Hann, Alexander |
author_sort | Egger, Jan |
collection | PubMed |
description | Ultrasound (US) is the most commonly used liver imaging modality worldwide. Due to its low cost, it is increasingly used in the follow-up of cancer patients with metastases localized in the liver. In this contribution, we present the results of an interactive segmentation approach for liver metastases in US acquisitions. A (semi-) automatic segmentation is still very challenging because of the low image quality and the low contrast between the metastasis and the surrounding liver tissue. Thus, the state of the art in clinical practice is still manual measurement and outlining of the metastases in the US images. We tackle the problem by providing an interactive segmentation approach providing real-time feedback of the segmentation results. The approach has been evaluated with typical US acquisitions from the clinical routine, and the datasets consisted of pancreatic cancer metastases. Even for difficult cases, satisfying segmentations results could be achieved because of the interactive real-time behavior of the approach. In total, 40 clinical images have been evaluated with our method by comparing the results against manual ground truth segmentations. This evaluation yielded to an average Dice Score of 85% and an average Hausdorff Distance of 13 pixels. |
format | Online Article Text |
id | pubmed-5429849 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-54298492017-05-15 Interactive Outlining of Pancreatic Cancer Liver Metastases in Ultrasound Images Egger, Jan Schmalstieg, Dieter Chen, Xiaojun Zoller, Wolfram G. Hann, Alexander Sci Rep Article Ultrasound (US) is the most commonly used liver imaging modality worldwide. Due to its low cost, it is increasingly used in the follow-up of cancer patients with metastases localized in the liver. In this contribution, we present the results of an interactive segmentation approach for liver metastases in US acquisitions. A (semi-) automatic segmentation is still very challenging because of the low image quality and the low contrast between the metastasis and the surrounding liver tissue. Thus, the state of the art in clinical practice is still manual measurement and outlining of the metastases in the US images. We tackle the problem by providing an interactive segmentation approach providing real-time feedback of the segmentation results. The approach has been evaluated with typical US acquisitions from the clinical routine, and the datasets consisted of pancreatic cancer metastases. Even for difficult cases, satisfying segmentations results could be achieved because of the interactive real-time behavior of the approach. In total, 40 clinical images have been evaluated with our method by comparing the results against manual ground truth segmentations. This evaluation yielded to an average Dice Score of 85% and an average Hausdorff Distance of 13 pixels. Nature Publishing Group UK 2017-04-18 /pmc/articles/PMC5429849/ /pubmed/28420871 http://dx.doi.org/10.1038/s41598-017-00940-z Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Egger, Jan Schmalstieg, Dieter Chen, Xiaojun Zoller, Wolfram G. Hann, Alexander Interactive Outlining of Pancreatic Cancer Liver Metastases in Ultrasound Images |
title | Interactive Outlining of Pancreatic Cancer Liver Metastases in Ultrasound Images |
title_full | Interactive Outlining of Pancreatic Cancer Liver Metastases in Ultrasound Images |
title_fullStr | Interactive Outlining of Pancreatic Cancer Liver Metastases in Ultrasound Images |
title_full_unstemmed | Interactive Outlining of Pancreatic Cancer Liver Metastases in Ultrasound Images |
title_short | Interactive Outlining of Pancreatic Cancer Liver Metastases in Ultrasound Images |
title_sort | interactive outlining of pancreatic cancer liver metastases in ultrasound images |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5429849/ https://www.ncbi.nlm.nih.gov/pubmed/28420871 http://dx.doi.org/10.1038/s41598-017-00940-z |
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