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Comparison of three breast imaging techniques using 4-AFC human observation study
Author(s): Shada Kazemi; Oliver Diaz; Premkumar Elangovan; Kevin Wells; Annika Lohstroh
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Paper Abstract

X-ray mammography is the gold standard for detecting malignancies in a breast cancer screening context. However, limited angle tomosynthesis has now started to be used in screening due to its ability to remove overlying image clutter. However, breast CT is a method, which can potentially remove all overlying clutter through the use of tomographic image reconstruction.

The aim of this work is to investigate whether breast cone-beam computed tomography (CBCT) can provide better lesion detectability compared to 2D mammography or digital breast tomosynthesis (DBT).

Lesions with a diameter of 4 mm, 5 mm and 6 mm have been inserted in a simulated breast phantom. In total 180 images are analysed, out of which 90 images contain lesions (equally divided between the 4 mm, 5mm and 6mm diameter lesions) and the rest represent normal breast tissues. The TIGRE (Tomographic Iterative GPU-based Reconstruction) has been used to simulate 360 projections and to reconstruct the images using the FeldKamp, Davis and Kress (FDK) algorithm. Scattered radiation and Poisson noise have also been added to the projections prior the image reconstruction.

In total 10 observers, some with, and some without experience of mammography images, have been used as observers for this preliminary 4AFC study. The analysis of the 4AFC study shows that the mean minimum detectable lesion size for the breast CBCT is 2.96±0.23 mm with a 95% confidence intervals of [2.73, 3.19].

Paper Details

Date Published: 9 March 2018
PDF: 6 pages
Proc. SPIE 10573, Medical Imaging 2018: Physics of Medical Imaging, 105735I (9 March 2018); doi: 10.1117/12.2293201
Show Author Affiliations
Shada Kazemi, Univ. of Surrey (United Kingdom)
Oliver Diaz, Univ. of Surrey (United Kingdom)
Univ. of Girona (Spain)
Premkumar Elangovan, Univ. of Surrey (United Kingdom)
Royal Surrey County Hospital (United Kingdom)
Kevin Wells, Univ. of Surrey (United Kingdom)
Annika Lohstroh, Univ. of Surrey (United Kingdom)

Published in SPIE Proceedings Vol. 10573:
Medical Imaging 2018: Physics of Medical Imaging
Joseph Y. Lo; Taly Gilat Schmidt; Guang-Hong Chen, Editor(s)

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