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Proceedings Paper

Development and application of a channelized Hotelling observer for DBT optimization on structured background test images with mass simulating targets
Author(s): Dimitar Petrov; Koen Michielsen; Lesley Cockmartin; Gouzhi Zhang; Kenneth Young; Nicholas Marshall; Hilde Bosmans
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Paper Abstract

Digital breast tomosynthesis (DBT) is a 3D mammography technique that promises better visualization of low contrast lesions than conventional 2D mammography. A wide range of parameters influence the diagnostic information in DBT images and a systematic means of DBT system optimization is needed. The gold standard for image quality assessment is to perform a human observer experiment with experienced readers. Using human observers for optimization is time consuming and not feasible for the large parameter space of DBT. Our goal was to develop a model observer (MO) that can predict human reading performance for standard detection tasks of target objects within a structured phantom and subsequently apply it in a first comparative study. The phantom consists of an acrylic semi-cylindrical container with acrylic spheres of different sizes and the remaining space filled with water. Three types of lesions were included: 3D printed spiculated and non-spiculated mass lesions along with calcification groups. The images of the two mass lesion types were reconstructed with 3 different reconstruction methods (FBP, FBP with SRSAR, MLTRpr) and read by human readers. A Channelized Hotelling model observer was created for the non-spiculated lesion detection task using five Laguerre-Gauss channels, tuned for better performance. For the non-spiculated mass lesions a linear relation between the MO and human observer results was found, with correlation coefficients of 0.956 for standard FBP, 0.998 for FBP with SRSAR and 0.940 for MLTRpr. Both the MO and human observer percentage correct results for the spiculated masses were close to 100%, and showed no difference from each other for every reconstruction algorithm.

Paper Details

Date Published: 24 March 2016
PDF: 9 pages
Proc. SPIE 9787, Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, 97871K (24 March 2016); doi: 10.1117/12.2216713
Show Author Affiliations
Dimitar Petrov, KU Leuven (Belgium)
Koen Michielsen, KU Leuven (Belgium)
Lesley Cockmartin, UZ Leuven (Belgium)
Gouzhi Zhang, UZ Leuven (Belgium)
Kenneth Young, The Royal Surrey County Hospital NHS Trust (United Kingdom)
Nicholas Marshall, UZ Leuven (Belgium)
Hilde Bosmans, UZ Leuven (Belgium)


Published in SPIE Proceedings Vol. 9787:
Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment
Craig K. Abbey; Matthew A. Kupinski, Editor(s)

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