Program Information
Utility of a Channelized Hotelling Model Observer Over a Large Range of Angiographic Exposure Levels
K Fetterly1*, C Favazza2 , (1) Mayo Clinic, Rochester, MN, (2) Mayo Clinic, Rochester, MN
Presentations
WE-G-204-2 (Wednesday, July 15, 2015) 4:30 PM - 6:00 PM Room: 204
Purpose:
Mathematical model observers provide a figure of merit that simultaneously considers a test object and the contrast, noise, and spatial resolution properties of an imaging system. The purpose of this work was to investigate the utility of a channelized Hotelling model observer (CHO) to assess system performance over a large range of angiographic exposure conditions.
Methods:
A 4 mm diameter disk shaped, iodine contrast test object was placed on a 20 cm thick Lucite phantom and 1204 image frames were acquired using fixed x-ray beam quality and for several detector target dose (DTD) values in the range 6 to 240 nGy. The CHO was implemented in the spatial domain utilizing 96 Gabor functions as channels. Detectability index (DI) estimates were calculated using the “resubstitution” and “holdout” methods to train the CHO. Also, DI values calculated using discrete subsets of the data were used to estimate a minimally biased DI as might be expected from an infinitely large dataset. The relationship between DI, independently measured CNR, and changes in results expected assuming a quantum limited detector were assessed over the DTD range.
Results:
CNR measurements demonstrated that the angiography system is not quantum limited due to relatively increasing contamination from electronic noise that reduces CNR for low DTD. Direct comparison of DI versus CNR indicates that the CHO relatively overestimates DI for low DTD and/or underestimates DI values for high DTD. The relative magnitude of the apparent bias error in the DI values was ~20% over the 40x DTD range investigated.
Conclusion:
For the angiography system investigated, the CHO can provide a minimally biased figure of merit if implemented over a restricted exposure range. However, bias leads to overestimates of DI for low exposures. This work emphasizes the need to verify CHO model performance during real-world application.
Contact Email: