27 February 2010 Toward validation of a 3D structured background model for breast imaging
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Proceedings Volume 7627, Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment; 762716 (2010); doi: 10.1117/12.844692
Event: SPIE Medical Imaging, 2010, San Diego, California, United States
Abstract
Breast tomosynthesis is a novel modality for breast imaging that aims to provide partial depth resolution of the tissue structure. In order to optimize tomosynthesis acquisition and reconstruction parameters, it is necessary to model the structured breast background. The purpose of this work was to investigate whether filtered noise could be used as a structure surrogate. Human performance in a SKE detection task was determined through 2-AFC experiments using tomosynthesis backgrounds extracted from 55 normal breasts. Mathematically defined lesions were projected and reconstructed using the same acquisition and reconstruction parameters as the clinical data. Signal diameters were 0.05, 0.2 and 0.8 cm. Performance in the center projection as well as a reconstructed slice through the signal center was determined. The gray-scale volume was binarized and attenuation coefficients of adipose or fibroglandular tissue were assigned to the voxels. This volume was then projected and reconstructed and performance of a pre-whitening observer was computed for the slice and center projections. Human performance in clinical backgrounds was predicted by a pre-whitening observer model, both in projection images and reconstructed slices. This indicates that pre-whitening observer performance is a good predictor of human performance and can be used to predict human performance in the simulated backgrounds. When comparing model observer performance in the two background types, comparable performance was found. This indicates that structured background based on filtered noise may be useful in tomosynthesis system optimization. In conclusion, for a SKE detection task, similar performance was reached in clinical and filtered noise backgrounds. This indicates that detection performance based on the filtered noise background model may be used to predict performance in actual breast backgrounds.
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I. Reiser, S. Lee, K. Little, R. M. Nishikawa, "Toward validation of a 3D structured background model for breast imaging", Proc. SPIE 7627, Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment, 762716 (27 February 2010); doi: 10.1117/12.844692; https://doi.org/10.1117/12.844692
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KEYWORDS
Breast

Performance modeling

3D modeling

Signal detection

Breast imaging

Tissues

Data modeling

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