Fundamental to the development and application of channelized Hotelling observer (CHO) models is the selection of the
region of interest (ROI) to evaluate. For assessment of medical imaging systems, reducing the ROI size can be
advantageous. Smaller ROIs enable a greater concentration of interrogable objects in a single phantom image, thereby
providing more information from a set of images and reducing the overall image acquisition burden. Additionally,
smaller ROIs may promote better assessment of clinical patient images as different patient anatomies present different
ROI constraints. To this end, we investigated the minimum ROI size that does not compromise the performance of the
CHO model. In this study, we evaluated both simulated images and phantom CT images to identify the minimum ROI
size that resulted in an accurate figure of merit (FOM) of the CHO’s performance. More specifically, the minimum ROI
size was evaluated as a function of the following: number of channels, spatial frequency and number of rotations of the
Gabor filters, size and contrast of the object, and magnitude of the image noise. Results demonstrate that a minimum
ROI size exists below which the CHO’s performance is grossly inaccurate. The minimum ROI size is shown to increase
with number of channels and be dictated by truncation of lower frequency filters. We developed a model to estimate the
minimum ROI size as a parameterized function of the number of orientations and spatial frequencies of the Gabor filters,
providing a guide for investigators to appropriately select parameters for model observer studies.
Andrea Ferrero, Christopher P. Favazza, Lifeng Yu, Shuai Leng, and Cynthia H. McCollough, "Practical implementation of channelized hotelling observers: effect of ROI size," Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101320G (Presented at SPIE Medical Imaging: February 13, 2017; Published: 9 March 2017); https://doi.org/10.1117/12.2255530.
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