Investigation on location-dependent detectability of a small mass for digital breast tomosynthesis evaluation

Changwoo Lee; Jongduk Baek; Subok Park

doi:10.1117/12.2216579

24 March 2016 Investigation on location-dependent detectability of a small mass for digital breast tomosynthesis evaluation

Changwoo Lee, Jongduk Baek, Subok Park

Author Affiliations +

Proceedings Volume 9787, Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment; 97870V (2016) https://doi.org/10.1117/12.2216579
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

Digital breast tomosynthesis (DBT) is an emerging imaging modality for improved breast cancer detection and diagnosis [1-5]. Numerous efforts have been made to find quantitative metrics associated with mammographic image quality assessment, such as the exponent β of anatomical noise power spectrum, glandularity, contrast noise ratio, etc. [6-8]. In addition, with the use of Fourier-domain detectability for a task-based assessment of DBT, a stationarity assumption on reconstructed image statistics was often made [9-11], resulting in the use of multiple regions-of-interest (ROIs) from different locations in order to increase sample size. While all these metrics provide some information on mammographic image characteristics and signal detection, the relationship between these metrics and detectability in DBT evaluation has not been fully understood. In this work, we investigated spatial-domain detectability trends and levels as a function of the number of slices N_s at three different ROI locations on the same image slice, where background statistics differ in terms of the aforementioned metrics. Detectabilities for the three ROI locations were calculated using multi-slice channelized Hotelling observers with 2D/3D Laguerre-Gauss channels. Our simulation results show that detectability levels and trends as a function of Ns vary across these three ROI locations. They also show that the exponent β, mean glandularity, and mean attenuation coefficient vary across the three ROI locations but they do not necessarily predict the ranking of detectability levels and trends across these ROI locations.

Citation Download Citation

Changwoo Lee, Jongduk Baek, and Subok Park "Investigation on location-dependent detectability of a small mass for digital breast tomosynthesis evaluation", Proc. SPIE 9787, Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, 97870V (24 March 2016); https://doi.org/10.1117/12.2216579

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