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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]. |
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CITATIONS
Cited by 1 scholarly publication.
Breast
Digital breast tomosynthesis
Mammography
Tissues
Monte Carlo methods
Sensors
Reconstruction algorithms
