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Multivariate Feature Selection of Image Descriptors Data for Breast Cancer with Computer-Assisted Diagnosis
Open AccessArticle

Detecting Breast Cancer with a Dual-Modality Device

1
Department of Radiology, 2 Military Hospital, Hospital Street, Wynberg 7800, South Africa
2
Medical Imaging Research Unit, University of Cape Town, Observatory 7925, South Africa
3
CapeRay Medical (Pty) Ltd, 51 Bell Crescent, Westlake Business Park 7945, South Africa
4
Department of Surgery, Groote Schuur Hospital and University of Cape Town, Observatory 7925, South Africa
*
Author to whom correspondence should be addressed.
Academic Editor: Tanya W. Moseley
Diagnostics 2017, 7(1), 17; https://doi.org/10.3390/diagnostics7010017
Received: 31 January 2017 / Revised: 9 March 2017 / Accepted: 16 March 2017 / Published: 18 March 2017
(This article belongs to the Special Issue Breast Imaging)
Although mammography has been the gold standard for the early detection of breast cancer, if a woman has dense breast tissue, a false negative diagnosis may occur. Breast ultrasound, whether hand-held or automated, is a useful adjunct to mammography but adds extra time and cost. The primary aim was to demonstrate that our second-generation Aceso system, which combines full-field digital mammography (FFDM) and automated breast ultrasound (ABUS) in a single platform, is able to produce improved quality images that provide clinically meaningful results. Aceso was first tested using two industry standards: a Contrast Detail Mammography (CDMAM) phantom to assess the FFDM images, and the CIRS 054GS phantom to evaluate the ABUS images. In addition, 25 women participated in a clinical trial: 14 were healthy volunteers, while 11 were patients referred by the breast clinic at Groote Schuur Hospital. The CDMAM phantom results showed the FFDM results were better than the European Reference (EUREF) standard of “acceptable” and were approaching “achievable”. The ABUS results showed a lateral and axial spatial resolution of 0.5 mm and an adequate depth penetration of 80 mm. Our second-generation Aceso system, with its improved quality of clinical FFDM and ABUS images, has demonstrated its potential for the early detection of breast cancer in a busy clinic. View Full-Text
Keywords: breast cancer; dense breasts; dual-modality imaging; full-field digital mammography (FFDM); automated breast ultrasound (ABUS) breast cancer; dense breasts; dual-modality imaging; full-field digital mammography (FFDM); automated breast ultrasound (ABUS)
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MDPI and ACS Style

Padia, K.; Douglas, T.S.; Cairncross, L.L.; Baasch, R.V.; Vaughan, C.L. Detecting Breast Cancer with a Dual-Modality Device. Diagnostics 2017, 7, 17.

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