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The modeling of the distance-dependent spatial resolution of SPECT imaging in the projector and backprojector pair used in iterative reconstruction improves the resulting slices both quantitatively and qualitatively. By using small, spatial-domain, convolution masks to model the blurring from one image plane to the next, Gaussian diffusion can markedly reduce the computational burden. The problem with Gaussian diffusion is that aliasing distorts the coefficients of the masks such that there can be a significant loss in the accuracy with which resolution is modeled. The use of integration of the probability density function of the Gaussian function over pixel boundaries as opposed to delta-function sampling, an effective value for the standard deviation of the Gaussian used in blurring from one plane to the next, and diffusion over multiple plane steps were investigated as possible methods to diminish the impact of aliasing on accuracy. For large pixel sizes the combined use of all three methods was determined to be needed to reduce the impact of aliasing on accuracy. As the pixel size decreases, the use of any of the methods results in a significant improvement in accuracy.

The determination of quantitative estimates of activity such as the maximum and total counts in a volume are influenced by the partial volume effect. The magnitude of this effect varies with the nonstationary spatial resolution inherent in SPECT imaging, the size and shape of the object, and the relative concentration of the object to its background. The objective of this investigation was to determine if frequency distance relationship (FDR) restoration filtering can reduce the impact of distance-dependent spatial resolution on the quantitation of activity. An analytical projector was used to incorporate attenuation and distance-dependent blurring when simulating a set of small hot spherical objects in a cylindrical attenuator. Reconstruction was performed by filtered backprojection (FBP) with Bellini's method of attenuation correction. The simulations were filtered by: 1) three-dimensional (3-D) Butterworth filtering; 2) stationary parametric Wiener filtering; and 3) FDR restoration filtering regularized using Gaussian and parametric Wiener filters. The criteria used to compare the accuracy of quantitation were the center count ratios (CCR's) and total count ratios (TCR's). Both were determined as the ratio of observed counts over true counts. Results showed that after FDR restoration the TCR's varied less with location, and for both CCR's and TCR's the bias decreased compared to Butterworth filtering.

A non-iterative SPECT reconstruction method is presented which consists of pre-processing the projection data for compensation of scatter, attenuation and the detector response prior to ramp filtered backprojection. Scatter is compensated for using the dual-photopeak window (DPW) method, attenuation is compensated for using Bellini's method, and compensation for the nonstationary detector response and noise suppression is performed with a frequency distance principle (FDP) Wiener filter. This approach was compared to a number of different processing methods using a Monte Carlo simulation study of an anthropomorphic digitized phantom of the liver and spleen. The DPW/FDP Wiener filtering method was shown to provide accurate quantitation of the liver as well as an increase in the ratio of tumor contrast to background noise as compared to Butterworth smoothing.

In view of the common existing problems in present video-to-video super-resolution reconstruction, this paper proposes a pioneering video-to-video super-resolution reconstruction algorithm based on segmentation and space-time regularisation to solve these problems. First, a video-to-video super-resolution reconstruction algorithm based on segmentation is proposed to eliminate reconstructed temporal ringing and to improve the times of reconstruction. Second, considering that image mosaic is involved in our proposed reconstruction algorithm, an improved fade-in and fade-out method is proposed to make the mosaic image looks more natural. At last, an improved space-time regularisation algorithm is put forward to remove noise and preserve image edge at the same time. Using several experiments, we prove that the proposed algorithm can achieve state-of-the -art reconstruction effect. [ABSTRACT FROM AUTHOR]

Background: The tryptophan-depleting enzyme indoleamine-2,3-dioxygenase (IDO) is critical for the regulation of immunotolerance and plays an important role in immune-associated skin diseases., Objectives: To analyse the level of IDO in condyloma acuminata (CA) and its role in this condition., Methods: IDO expression was assessed in the skin and peripheral blood of healthy controls and patients with CA. To assess the role of skin IDO in immunity, the ability of isolated epidermal cells to metabolize tryptophan and the influence on polyclonal T-cell mitogen (PHA)-stimulated T-cell proliferation were explored., Results: IDO median fluorescence intensities in peripheral blood mononuclear cells from patients with CA were similar to those from healthy controls. Immunohistochemistry showed that IDO + cells were rare in normal skin and the control skin of patients with CA, but were greatly accumulated in wart tissue. Most fluorescence signals of IDO + cells did not overlap with those of CD1a + Langerhans cells. Human papillomavirus (HPV) DNA probe in situ hybridization showed a large number of IDO + cells in the HPV - site. Keratinocytes in the skin of healthy controls and the circumcised skin of patients with CA could minimally transform tryptophan into kynurenine, but IDO-competent epidermal cells from warts could transform tryptophan. In addition, these IDO-competent epidermal cells could inhibit PHA-stimulated T-cell proliferation. The addition of an IDO inhibitor, 1-methyl-d-tryptophan, restored the inhibited T-cell proliferation., Conclusions: Abnormally localized high IDO expression might be involved in the formation of a local immunotolerant microenvironment., (© 2017 British Association of Dermatologists.)

In maximum-likelihood expectation-maximization (MLEM) reconstruction of SPECT images, if both attenuation correction (AC) and detector response correction (DRC) are included, the reconstruction can be too time consuming to be clinically useful. With use of the ordered-subset expectation-maximization (OSEM) reconstruction, it has been reported that the reconstruction time can be substantially reduced. We investigated the reconstruction of point sources in a non-uniform attenuation medium in terms of the normalized FWHM of these sources. We compared MLEM versus OSEM reconstructions; circular versus elliptical orbits; and the presence versus the absence of background activity in the object. We found: (i) that OSEM does speed up the reconstruction by a factor of 10 over MLEM; (ii) that the resolution recovery does not depend on the type of orbit if both AC and DRC are included in the reconstruction; however, when there is background activity, a significant number of iterations are required to alleviate the effect of orbit; (iii) that background activity significantly slows down the resolution recovery of the point sources; and (iv) that if reconstruction only includes AC, and not DRC, changing orbit can change isotropy of recovered resolution, whereas introducing background activity may degrade the recovered resolution and also changes the isotropy.

Background: In single photon-emission computed tomographic imaging of the chest, nonuniform attenuation correction requires use of a patient-specific attenuation map. The aim of this study was to determine whether an estimate of the regions of the lungs and nonpulmonary tissues of the chest could be obtained by segmenting the photopeak and Compton scatter window images in a phantom and in patients to estimate patient-specific attenuation maps., Methods and Results: The photopeak and scatter window slices from 16 consecutive 99mTc-labeled sestamibi perfusion studies were segmented interactively. In these studies, visually reasonable regions could be obtained by estimating a "cold" lung region from scatter window data with additional anatomic information of the myocardium region, the backbone and sternum locations, the liver, and the rib cage from the photopeak window data. In an anthropomorphic torso phantom study and a patient study, comparison was made between the attenuation maps based on segmentation of the emission images and transmission imaging with a slant-hole collimator. It was determined that good agreement in the estimation of the body regions can be achieved with segmentation of the emission images in both the phantom and patient data. Attenuation correction using the maximum-likelihood expectation maximization method was performed on the phantom and the patient data. In both studies, attenuation correction with the segmented attenuation map improved uniformity of the inferior wall region in comparison with the other walls., Conclusions: The estimation of patient-specific attenuation maps by segmenting the scatter and photopeak window slices of 99mTc-labeled sestamibi studies may be a way of reducing the loss of specificity due to attenuation artifacts. The potential limitations on the accuracy of correction inherent in the method due to the estimation of the regions and assignment of the attenuation coefficients need to be determined further, and the method needs to be further automated before it can be considered for routine clinical use.

We define two forms of stochastic tomography. In global tomography, the goal is to reconstruct an object from noisy observations of all of its projections. In region-of-interest (ROI) tomography, the goal is to reconstruct a small portion of an object (an ROI) from noisy observations of its projections densely sampled in and near the ROI and sparsely sampled away from the ROI. We solve both problems by expanding the object and its projections in a circular harmonic (Fourier) series in the angular variable so that the Radon transform becomes Abel transforms of integer orders applied to the harmonics. The algorithm has three major components. First, we fit state-space models to each order of Abel transform and thus represent the Radon transform operation as a parallel bank of systems, each of which computes the appropriate Abel transform of a circular harmonic. A variable transformation here allows either the global or ROI problem to be solved. Second, the object harmonics are modeled as a Brownian branch. This is a two-point boundary value system, which is Markovianized into a form suitable for the Kalman filter. Finally, a parallel bank of Kalman smoothing filters independently estimates each circular harmonic from the noisy projection data. Numerical examples illustrate the proposed procedure.

To study the hypothalamic control of growth hormone (GH) release in lower vertebrates, we employed an in vitro technique using a monolayer cell culture system of rainbow trout pituitary glands. Two newly purified carp brain growth hormone-releasing factors, carp GRF(1-45) and carp GRF(1-29), and synthetic somatostatin-14 (SST-14) were applied to the cultured pituitary cells. The results indicate that: (1) The carp GRFs had a dose-related potency in stimulating growth hormone release. The dose of half maximum effect (ED50) for carp GRF(1-45) was 0.107 nM, and an equal potency for carp GRF(1-29) was 0.388 nM. (2) SST-14 inhibited GH release having a dose-dependent potency with an ED50 of 0.186 nM. (3) Osmotic pressure did not influence SST-14 inhibited GH secretion but did affect spontaneous GH release. (4) The response of cultured cells was not affected by length of incubation period with SST-14 or carp GRF but was affected by cell density.