The channelized-Hotelling observer (CHO) was investigated on the ability to predict the human detection performance in order to assess clinical image quality objectively. CHO applied three user-selectable difference of Gaussian (DoG) channels on the images. The choice of the parameter values that comprise the DoG channel-sets of the CHO was investigated. In order to select the optimal channels, the CHO performance was compared to that of humans who scored digital mammography (DM) images in 2-alternative forced choice experiments. Square regions-of-interest (ROI)s from DM images of an anthropomorphic breast phantom with and without calcification-like signals were extracted. Images at four dose levels were acquired and the resulting signal detectability was assessed using the CHO with various DoG channel parameters. It was found that varying these parameter values affects the correlation (r²) of the CHO with human observers for the detection task investigated. It appears that the DoG channel-sets need to be adapted to the frequency content of the signals and backgrounds present in the DM images.