**Publications**(67)

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Knowledge of the principles of image science is essential to the successful application of artificial intelligence in medical imaging.

_{2}:Eu . Poisson light is expected to yield zero temporal correlations, while super-Poisson light is expected to yield positive, and sub-Poisson light is expected to yield negative temporal correlation. Scintillation light in SrI

_{2}:Eu was found to be negatively correlated. Therefore, we conclude that the scintillation light in SrI

_{2}:Eu is sub-Poisson.

^{3}R. The FastSPECT II system consisted of two rings of eight scintillation cameras each. The resulting dimensions of H were 68921 voxels by 97344 detector pixels. The M

^{3}R system is a four camera system that was reconfigured to measure image space using a single scintillation camera. The resulting dimensions of H were 50864 voxels by 6241 detector pixels. In this paper we present results of the SVD of each system and discuss calculation of the measurement and null space for each system.

^{1}. The Hotelling detector, which is a prewhitening matched filter, calculates the Hotelling test statistic which is then compared to a threshold. If the test statistic is greater than the threshold the algorithm decides that a companion is present. This decision is the main task performed by the Hotelling observer. After a detection is made the location and intensity of the companion which maximise this test statistic are taken as the estimated values. We compare the Hotelling approach with current detection algorithms widely used in astronomy. We discuss the use of the estimation receiver operating characteristic (EROC) curve in quantifying the performance of the algorithm with no prior estimate of the companion's location or intensity. The robustness of this technique to errors in point spread function (PSF) estimation is also investigated.

*μm*intrinsic resolutions.

^{1-7}These detectors show great promise in small-animal SPECT and molecular imaging and exist in a variety of cofigurations. Typically, a columnar CsI(Tl) scintillator or a radiography screen (Gd

_{2}O

_{2}S:Tb) is imaged onto the CCD. Gamma-ray interactions are seen as clusters of signal spread over multiple pixels. When the detector is operated in a charge-integration mode, signal spread across pixels results in spatial-resolution degradation. However, if the detector is operated in photon-counting mode, the gamma-ray interaction position can be estimated using either Anger (centroid) estimation or maximum-likelihood position estimation resulting in a substantial improvement in spatial resolution.

^{2}Due to the low-light-level nature of the scintillation process, CCD-based gamma cameras implement an amplfication stage in the CCD via electron multiplying (EMCCDs)

^{8-10}or via an image intensfier prior to the optical path.

^{1}We have applied ideas and techniques from previous systems to our high-resolution LumiSPECT detector.

^{11, 12}LumiSPECT is a dual-modality optical/SPECT small-animal imaging system which was originally designed to operate in charge-integration mode. It employs a cryogenically cooled, high-quantum-efficiency, back-illuminated large-format CCD and operates in single-photon-counting mode without any intermediate amplfication process. Operating in photon-counting mode, the detector has an intrinsic spatial resolution of 64

*μm*compared to 134

*μm*in integrating mode.

*D*Laguerre-Gauss and difference-of-Gaussian channels to calculate area under the receiver-operating characteristic curve (AUC). Previous work presented at this meeting described a unique, small-animal SPECT system (M

^{3}R) capable of operating under a myriad of hardware configurations and ideally suited for image quality studies. Measured system matrices were collected for several hardware configurations of M

^{3}R. The data used to implement these two methods was then generated by taking simulated objects through the measured system matrices. The results of these two methods comprise a combination of qualitative and quantitative analysis that is well-suited for hardware assessment.

Evaluating estimation techniques in medical imaging without a gold standard: experimental validation

_{a}, using a well-known formula involving an error function. The ROC curve can also be determined by psychophysical studies for humans performing the same task, and again figures of merit such as AUC and d

_{z}can be derived. Since the likelihood ratio is optimal, however, the d

_{a}values for the human must necessarily be less than those for the ideal observer, and the square of the ratio of d

_{a}(human)/d

_{a}(ideal) is frequently taken as a measure of the perceptual efficiency of the human. The applicability of this efficiency measure is limited, however, since there are very few problems for which we can actually compute d

_{a}or AUC for the ideal observer. In this paper we examine some basic mathematical properties of the likelihood ratio and its logarithm. We demonstrate that there are strong constraints on the form of the probability density functions for these test statistics. In fact, if one knows, say, the density on the logarithm of the likelihood ratio under the null hypothesis, the densities of both the likelihood and the log-likelihood under both hypotheses are specified in terms of a likelihood-generating function. From this single function one can obtain all moments of both the likelihood and the log-likelihood under both hypotheses. Moreover, a AUC is expressed to an excellent approximation by a single point on the function. We illustrate these mathematical properties by considering the problem of signal detection with uncertain signal location.

^{99m}Tc. The results are in good agreement with the model for signal induction.

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