Automated quality assessment in three-dimensional breast ultrasound images
Automated three-dimensional breast ultrasound (ABUS) is a valuable adjunct to x-ray mammography for breast cancer screening of women with dense breasts. High image quality is essential for proper diagnostics and computer-aided detection. We propose an automated image quality assessment system for AB...
| Authors: | ; ; ; ; ; ; ; ; |
|---|---|
| Format: | Article |
| Status: | Published version |
| Publication date: | 2016 |
| Country: | España |
| Institution: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repository: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10256/18461 |
| Online Access: | http://hdl.handle.net/10256/18461 |
| Access Level: | Open access |
| Keyword: | Mama -- Ecografia Breast -- Ultrasonic imaging Imatges -- Processament Imatgeria per al diagnòstic Diagnostic imaging Mama -- Càncer Breast -- Cancer |
| _version_ | 1878731383932715008 |
|---|---|
| author | Schwaab, Julia |
| author2 | Diez, Yago Oliver i Malagelada, Arnau Martí Marly, Robert Zelst, Jan Van Gubern Mérida, Albert Mourri, Ahmed Bensouda Gregori, Johannes Günther, Matthias |
| author2_role | author author author author author author author author |
| author_browse | Diez, Yago Gregori, Johannes Gubern Mérida, Albert Günther, Matthias Martí Marly, Robert Mourri, Ahmed Bensouda Oliver i Malagelada, Arnau Schwaab, Julia Zelst, Jan Van |
| author_facet | Schwaab, Julia Diez, Yago Oliver i Malagelada, Arnau Martí Marly, Robert Zelst, Jan Van Gubern Mérida, Albert Mourri, Ahmed Bensouda Gregori, Johannes Günther, Matthias |
| author_role | author |
| collection | Recercat. Dipósit de la Recerca de Catalunya |
| description | Automated three-dimensional breast ultrasound (ABUS) is a valuable adjunct to x-ray mammography for breast cancer screening of women with dense breasts. High image quality is essential for proper diagnostics and computer-aided detection. We propose an automated image quality assessment system for ABUS images that detects artifacts at the time of acquisition. Therefore, we study three aspects that can corrupt ABUS images: the nipple position relative to the rest of the breast, the shadow caused by the nipple, and the shape of the breast contour on the image. Image processing and machine learning algorithms are combined to detect these artifacts based on 368 clinical ABUS images that have been rated manually by two experienced clinicians. At a specificity of 0.99, 55% of the images that were rated as low quality are detected by the proposed algorithms. The areas under the ROC curves of the single classifiers are 0.99 for the nipple position, 0.84 for the nipple shadow, and 0.89 for the breast contour shape. The proposed algorithms work fast and reliably, which makes them adequate for online evaluation of image quality during acquisition. The presented concept may be extended to further image modalities and quality aspects |
| eu_rights_str_mv | openAccess |
| format | article |
| id | ES_2e7aadccd665db7635e237fc7a7ffb39 |
| institution | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| instname_str | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| network_acronym_str | ES |
| network_name_str | España |
| oai_identifier_str | oai:recercat.cat:10256/18461 |
| publishDate | 2016 |
| publishDateSort | 2016 |
| publisher | Society of Photo-optical Instrumentation Engineers (SPIE) |
| publisherStr | Society of Photo-optical Instrumentation Engineers (SPIE) |
| reponame_str | Recercat. Dipósit de la Recerca de Catalunya |
| spelling | Automated quality assessment in three-dimensional breast ultrasound images Schwaab, Julia Diez, Yago Oliver i Malagelada, Arnau Martí Marly, Robert Zelst, Jan Van Gubern Mérida, Albert Mourri, Ahmed Bensouda Gregori, Johannes Günther, Matthias Mama -- Ecografia Breast -- Ultrasonic imaging Imatges -- Processament Imatgeria per al diagnòstic Diagnostic imaging Mama -- Càncer Breast -- Cancer Automated three-dimensional breast ultrasound (ABUS) is a valuable adjunct to x-ray mammography for breast cancer screening of women with dense breasts. High image quality is essential for proper diagnostics and computer-aided detection. We propose an automated image quality assessment system for ABUS images that detects artifacts at the time of acquisition. Therefore, we study three aspects that can corrupt ABUS images: the nipple position relative to the rest of the breast, the shadow caused by the nipple, and the shape of the breast contour on the image. Image processing and machine learning algorithms are combined to detect these artifacts based on 368 clinical ABUS images that have been rated manually by two experienced clinicians. At a specificity of 0.99, 55% of the images that were rated as low quality are detected by the proposed algorithms. The areas under the ROC curves of the single classifiers are 0.99 for the nipple position, 0.84 for the nipple shadow, and 0.89 for the breast contour shape. The proposed algorithms work fast and reliably, which makes them adequate for online evaluation of image quality during acquisition. The presented concept may be extended to further image modalities and quality aspects Society of Photo-optical Instrumentation Engineers (SPIE) http://hdl.handle.net/10256/18461 |
| spellingShingle | Automated quality assessment in three-dimensional breast ultrasound images Schwaab, Julia Mama -- Ecografia Breast -- Ultrasonic imaging Imatges -- Processament Imatgeria per al diagnòstic Diagnostic imaging Mama -- Càncer Breast -- Cancer |
| status_str | publishedVersion |
| title | Automated quality assessment in three-dimensional breast ultrasound images |
| title_full | Automated quality assessment in three-dimensional breast ultrasound images |
| title_fullStr | Automated quality assessment in three-dimensional breast ultrasound images |
| title_full_unstemmed | Automated quality assessment in three-dimensional breast ultrasound images |
| title_short | Automated quality assessment in three-dimensional breast ultrasound images |
| title_sort | Automated quality assessment in three-dimensional breast ultrasound images |
| topic | Mama -- Ecografia Breast -- Ultrasonic imaging Imatges -- Processament Imatgeria per al diagnòstic Diagnostic imaging Mama -- Càncer Breast -- Cancer |
| topic_facet | Mama -- Ecografia Breast -- Ultrasonic imaging Imatges -- Processament Imatgeria per al diagnòstic Diagnostic imaging Mama -- Càncer Breast -- Cancer |
| url | http://hdl.handle.net/10256/18461 |