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Can a channelized Hotelling observer assess image quality in acquired mammographic images of an anthropomorphic breast phantom including image processing?
Author(s) -
Balta C.,
Bouwman R. W.,
Sechopoulos I.,
Broeders M. J. M.,
Karssemeijer N.,
Engen R. E.,
Veldkamp W. J. H.
Publication year - 2019
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1002/mp.13342
Subject(s) - imaging phantom , image quality , mammography , artificial intelligence , observer (physics) , channelized , pixel , computer vision , computer science , image processing , digital mammography , pattern recognition (psychology) , nuclear medicine , mathematics , image (mathematics) , medicine , physics , breast cancer , telecommunications , cancer , quantum mechanics
Purpose To study the feasibility of a channelized Hotelling observer (CHO) to predict human observer performance in detecting calcification‐like signals in mammography images of an anthropomorphic breast phantom, as part of a quality control (QC) framework. Methods A prototype anthropomorphic breast phantom with inserted gold disks of 0.25 mm diameter was imaged with two different digital mammography x‐ray systems at four different dose levels. Regions of interest (ROIs) were extracted from the acquired processed and unprocessed images, signal‐present and signal‐absent. The ROIs were evaluated by a CHO using four different formulations of the difference of Gaussian (DoG) channel sets. Three human observers scored the ROIs in a two‐alternative forced‐choice experiment. We compared the human and the CHO performance on the simple task to detect calcification‐like disks in ROIs with and without postprocessing. The proportion of correct responses of the human reader (PC H ) and the CHO (PC CHO ) was calculated and the correlation between the two was analyzed using a mixed‐effect regression model. To address the signal location uncertainty, the impact of shifting the DoG channel sets in all directions up to two pixels was evaluated. Correlation results including the goodness of fit (r 2 ) of PC H and PC CHO for all different parameters were evaluated. Results Subanalysis by system yielded strong correlations between PC H and PC CHO , with r 2 between PC H and PC CHO was found to be between 0.926 and 0.958 for the unshifted and between 0.759 and 0.938 for the shifted channel sets, respectively. However, the linear fit suggested a slight system dependence. PC CHO with shifted channel sets increased CHO performance but the correlation with humans was decreased. These correlations were not considerably affected by of the DoG channel set used. Conclusions There is potential for the CHO to be used in QC for the evaluation of detectability of calcification‐like signals. The CHO can predict the PC of humans in images of calcification‐like signals of two different systems. However, a global model to be used for all systems requires further investigation.