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Journal of Medical Imaging • Open Access

Automated quality assessment in three-dimensional breast ultrasound images
Author(s): Julia Schwaab; Yago Diez; Arnau Oliver; Robert Martí; Jan van Zelst; Albert Gubern-Mérida; Ahmed Bensouda Mourri; Johannes Gregori; Matthias Günther

Paper Abstract

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.

Paper Details

Date Published: 25 April 2016
PDF: 11 pages
J. Med. Imag. 3(2) 027002 doi: 10.1117/1.JMI.3.2.027002
Published in: Journal of Medical Imaging Volume 3, Issue 2
Show Author Affiliations
Julia Schwaab, mediri GmbH (Germany)
Yago Diez, Tohoku Univ. (Japan)
Arnau Oliver, Univ. de Girona (Spain)
Robert Martí, Univ. de Girona (Spain)
Jan van Zelst, Radboud Univ. Medical Ctr. (Netherlands)
Albert Gubern-Mérida, Radboud Univ. Medical Ctr. (Netherlands)
Ahmed Bensouda Mourri, Univ. Libre de Bruxelles (Belgium)
Johannes Gregori, mediri GmbH (Germany)
Matthias Günther, mediri GmbH (Germany)
Fraunhofer MEVIS (Germany)

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