Noise Simulations For an Inverse-Geometry Volumetric CT System

This paper examines the noise performance of an inverse-geometry volumetric CT (IGCT) scanner through simulations. The IGCT system uses a large area scanned source and a smaller array of detectors to rapidly acquire volumetric data with negligible cone-beam artifacts. The first investigation compares the photon efficiency of the IGCT geometry to a 2D parallel ray system. The second investigation models the photon output of the IGCT source and calculates the expected noise. For the photon efficiency investigation. the same total number of photons was modeled in an IGCT acquisition and a comparable multi-slice 2D parallel ray acquisition. For both cases noise projections were simulated and the central axial slice reconstructed. In the second study. to investigate the noise in an IGCT system, the expected x-ray photon flux was modeled and projections simulated through ellipsoid phantoms. All simulations were compared to theoretical predictions. The results of the photon efficiency simulations verify that the IGCT geometry is as efficient in photon utilization as a 2D parallel ray geometry. For a 10 cm diameter 4 cm thick ellipsoid water phantom and for reasonable system parameters, the calculated standard deviation was approximately 15 HU at the center of the ellipsoid. For the same size phantom with maximum attenuation equivalent to 30 cm of water, the calculated noise was approximately 131 HU. The theoretical noise predictions for these objects were 15 HU and 112 HU respectively. These results predict acceptable noise levels for a system with a 0.16 second scan time and 12 lp/cm isotropic resolution

Three-Dimensional Reconstruction Algorithm for a Reverse-Geometry Volumetric CT System With a Large-Array Scanned Source

We have proposed a CT system design to rapidly produce volumetric images with negligible cone beam artifacts. The investigated system uses a large array scanned source with a smaller array of fast detectors. The x-ray source is electronically steered across a 2D target every few milliseconds as the system rotates. The proposed reconstruction algorithm for this system is a modified 3D filtered backprojection method. The data are rebinned into 2D parallel ray projections, most of which are tilted with respect to the axis of rotation. Each projection is filtered with a 2D kernel and backprojected onto the desired image matrix. To ensure adequate spatial resolution and low artifact level, we rebin the data onto an array that has sufficiently fine spatial and angular sampling. Due to finite sampling in the real system, some of the rebinned projections will be sparse, but we hypothesize that the large number of views will compensate for the data missing in a particular view. Preliminary results using simulated data with the expected discrete sampling of the source and detector arrays suggest that high resolution

Cryopreservation by pellet freezing of epididymal and ejaculated spermatozoa from male dogs

In this study, I evaluated the cryopreservation by pellet freezing of spermatozoa from individual dogs. In Experiment I, spermatozoa from 15 pairs of epididymides were suspended in glycerol, frozen as pellets of 10, 50, 100, or 200 μl volumes, and thawed by dilution with TALP (Tyrode\u27s solution plus albumin, lactate, pyruvate). In Experiment II, spermatozoa from 16 pairs of epididymides were suspended in glycerol, dimethyl sulfoxide, or ethylene glycol, frozen as 100 μl pellets, and thawed by dilution with TALP, canine capacitation medium (CCM), or 3% sodium citrate solution. In Experiment III, spermatozoa from 15 pairs of epididymides were suspended in glycerol, frozen as 100 μl pellets, and thawed by dilution with CCM. In Experiment IV, ejaculated spermatozoa from each of three dogs and epididymal spermatozoa from each of four other dogs were suspended in glycerol and were frozen and thawed as in Experiment III. Survival was determined by microscopic evaluation of motility and of membrane integrity. In Experiments III and IV, survival was also assayed by measuring the zona-binding capacity of the spermatozoa. Survival of frozen-thawed samples was significantly lower than unfrozen samples. Sperm survival after freezing depended significantly on the pellet volume, reflecting the effect of cooling rate as a function of pellet volume. Thawing solutions and CPAs also significantly affected post-thaw sperm survival. The highest post-thaw survival was obtained with a pellet volume of 100 μl and with the CPA-thawing solution combinations of glycerol-CCM and glycerol-TALP. The number of membrane-intact spermatozoa bound to each oocyte was significantly higher for unfrozen samples than for frozen-thawed samples. Ejaculated spermatozoa exhibited survival and zona-binding capacity similar to that of epididymal spermatozoa, and there was little variation in the survival of ejaculated spermatozoa from an individual dog. There were significant differences in post-thaw sperm survival and zona-binding capacity among individual dogs. These results complement previous studies showing male-to-male differences in freezing susceptibility of canine spermatozoa

Tenfold your photons -- a physically-sound approach to filtering-based variance reduction of Monte-Carlo-simulated dose distributions

X-ray dose constantly gains interest in the interventional suite. With dose being generally difficult to monitor reliably, fast computational methods are desirable. A major drawback of the gold standard based on Monte Carlo (MC) methods is its computational complexity. Besides common variance reduction techniques, filter approaches are often applied to achieve conclusive results within a fraction of time. Inspired by these methods, we propose a novel approach. We down-sample the target volume based on the fraction of mass, simulate the imaging situation, and then revert the down-sampling. To this end, the dose is weighted by the mass energy absorption, up-sampled, and distributed using a guided filter. Eventually, the weighting is inverted resulting in accurate high resolution dose distributions. The approach has the potential to considerably speed-up MC simulations since less photons and boundary checks are necessary. First experiments substantiate these assumptions. We achieve a median accuracy of 96.7 % to 97.4 % of the dose estimation with the proposed method and a down-sampling factor of 8 and 4, respectively. While maintaining a high accuracy, the proposed method provides for a tenfold speed-up. The overall findings suggest the conclusion that the proposed method has the potential to allow for further efficiency.Comment: 6 pages, 3 figures, Bildverarbeitung f\"ur die Medizin 202

Obstruction of biodiversity conservation by minimum patch size criteria.

Minimum patch size criteria for habitat protection reflect the conservation principle that a single large (SL) patch of habitat has higher biodiversity than several small (SS) patches of the same total area (SL > SS). Nonetheless, this principle is often incorrect, and biodiversity conservation requires placing more emphasis on protection of large numbers of small patches (SS > SL). We used a global database reporting the abundances of species across hundreds of patches to assess the SL > SS principle in systems where small patches are much smaller than the typical minimum patch size criteria applied for biodiversity conservation (i.e., ∼85% of patches <100 ha). The 76 metacommunities we examined included 4401 species in 1190 patches. From each metacommunity, we resampled species-area accumulation curves to evaluate how biodiversity responded to habitat existing as a few large patches or as many small patches. Counter to the SL > SS principle and consistent with previous syntheses, species richness accumulated more rapidly when adding several small patches (45.2% SS > SL vs. 19.9% SL > SS) to reach the same cumulative area, even for the very small patches in our data set. Responses of taxa to habitat fragmentation differed, which suggests that when a given total area of habitat is to be protected, overall biodiversity conservation will be most effective if that habitat is composed of as many small patches as possible, plus a few large ones. Because minimum patch size criteria often require larger patches than the small patches we examined, our results suggest that such criteria hinder efforts to protect biodiversity

Precision Learning: Towards Use of Known Operators in Neural Networks

In this paper, we consider the use of prior knowledge within neural networks. In particular, we investigate the effect of a known transform within the mapping from input data space to the output domain. We demonstrate that use of known transforms is able to change maximal error bounds. In order to explore the effect further, we consider the problem of X-ray material decomposition as an example to incorporate additional prior knowledge. We demonstrate that inclusion of a non-linear function known from the physical properties of the system is able to reduce prediction errors therewith improving prediction quality from SSIM values of 0.54 to 0.88. This approach is applicable to a wide set of applications in physics and signal processing that provide prior knowledge on such transforms. Also maximal error estimation and network understanding could be facilitated within the context of precision learning.Comment: accepted on ICPR 201

Geometry Analysis of an Inverse-Geometry Volumetric CT System With Multiple Detector Arrays

An inverse-geometry volumetric CT (IGCT) system for imaging in a single fast rotation without cone-beam artifacts is being developed. It employs a large scanned source array and a smaller detector array. For a single-source/single-detector implementation, the FOV is limited to a fraction of the source size. Here we explore options to increase the FOV without increasing the source size by using multiple detectors spaced apart laterally to increase the range of radial distances sampled. We also look at multiple source array systems for faster scans. To properly reconstruct the FOV, Radon space must be sufficiently covered and sampled in a uniform manner. Optimal placement of the detectors relative to the source was determined analytically given system constraints (5cm detector width, 25cm source width, 45cm source-to-isocenter distance). For a 1x3 system (three detectors per source) detector spacing (DS) was 18deg and source-to-detector distances (SDD) were 113, 100 and 113cm to provide optimum Radon sampling and a FOV of 44cm. For multiple-source systems, maximum angular spacing between sources cannot exceed 125deg since detectors corresponding to one source cannot be occluded by a second source. Therefore, for 2x3 and 3x3 systems using the above DS and SDD, optimum spacing between sources is 115deg and 61deg respectively, requiring minimum scan rotations of 115deg and 107deg. Also, a 3x3 system can be much faster for full 360deg dataset scans than a 2x3 system (120deg vs. 245deg). We found that a significantly increased FOV can be achieved while maintaining uniform radial sampling as well as a substantial reduction in scan time using several different geometries. Further multi-parameter optimization is underway

An Efficient Estimation Method for Reducing the Axial Intensity Drop in Circular Cone-Beam CT

Reconstruction algorithms for circular cone-beam (CB) scans have been extensively studied in the literature. Since insufficient data are measured, an exact reconstruction is impossible for such a geometry. If the reconstruction algorithm assumes zeros for the missing data, such as the standard FDK algorithm, a major type of resulting CB artifacts is the intensity drop along the axial direction. Many algorithms have been proposed to improve image quality when faced with this problem of data missing; however, development of an effective and computationally efficient algorithm remains a major challenge. In this work, we propose a novel method for estimating the unmeasured data and reducing the intensity drop artifacts. Each CB projection is analyzed in the Radon space via Grangeat's first derivative. Assuming the CB projection is taken from a parallel beam geometry, we extract those data that reside in the unmeasured region of the Radon space. These data are then used as in a parallel beam geometry to calculate a correction term, which is added together with Hu's correction term to the FDK result to form a final reconstruction. More approximations are then made on the calculation of the additional term, and the final formula is implemented very efficiently. The algorithm performance is evaluated using computer simulations on analytical phantoms. The reconstruction comparison with results using other existing algorithms shows that the proposed algorithm achieves a superior performance on the reduction of axial intensity drop artifacts with a high computation efficiency