This study quantitatively evaluated the performance of the exponential transformation of the free-response operating characteristic curve (EFROC) metric, with the Channelized Hotelling Observer (CHO) as a reference. The CHO has been used for image quality assessment of reconstruction algorithms and imaging systems and often it is applied to study the signal-location-known cases. The CHO also requires a large set of images to estimate the covariance matrix. In terms of clinical applications, this assumption and requirement may be unrealistic. The newly developed location-unknown EFROC detectability metric is estimated from the confidence scores reported by a model observer. Unlike the CHO, EFROC does not require a channelization step and is a non-parametric detectability metric. There are few quantitative studies available on application of the EFROC metric, most of which are based on simulation data. This study investigated the EFROC metric using experimental CT data. A phantom with four low contrast objects: 3mm (14 HU), 5mm (7HU), 7mm (5 HU) and 10 mm (3 HU) was scanned at dose levels ranging from 25 mAs to 270 mAs and reconstructed using filtered backprojection. The area under the curve values for CHO (AUC) and EFROC (AFE) were plotted with respect to different dose levels. The number of images required to estimate the non-parametric AFE metric was calculated for varying tasks and found to be less than the number of images required for parametric CHO estimation. The AFE metric was found to be more sensitive to changes in dose than the CHO metric. This increased sensitivity and the assumption of unknown signal location may be useful for investigating and optimizing CT imaging methods. Future work is required to validate the AFE metric against human observers.
[1]
Kyle J Myers,et al.
CT image assessment by low contrast signal detectability evaluation with unknown signal location.
,
2013,
Medical physics.
[2]
Shuai Leng,et al.
Prediction of human observer performance in a 2-alternative forced choice low-contrast detection task using channelized Hotelling observer: impact of radiation dose and reconstruction algorithms.
,
2013,
Medical physics.
[3]
L. Popescu.
Nonparametric signal detectability evaluation using an exponential transformation of the FROC curve.
,
2011,
Medical physics.
[4]
Matthew A Kupinski,et al.
Assessing image quality and dose reduction of a new x-ray computed tomography iterative reconstruction algorithm using model observers.
,
2014,
Medical physics.
[5]
D. C. Barber,et al.
Medical Imaging-The Assessment of Image Quality
,
1996
.
[6]
Taly Gilat Schmidt,et al.
Reducing radiation dose to the female breast during CT coronary angiography: a simulation study comparing breast shielding, angular tube current modulation, reduced kV, and partial angle protocols using an unknown-location signal-detectability metric.
,
2013,
Medical physics.