Divisive normalization in channelized Hotelling observer

Channelized Hotelling observers have been evaluated in signal detection in medical images. However, these model observers fall short of overestimate of detection performance compared with human observers. Here, we present a modified channelized Hotelling observer with divisive normalization mechanism. In this model, images first traverse a series of Gabor filters of different orientations, phases and spatial frequencies. Then, the channels outputs pass through a nonlinear process and pool in several channels. Finally, these channels responses are normalized through a divisive operation. Human performances of nodule detection in chest radiography are evaluated by 2AFC experiments. The same detection tasks are performed by the model observers. The results show that the modified channelized Hotelling observer can well predict the human performances.