Phantom studies demonstrated superior resolution and noise properties for the Sharp and UHR modes relative to the standard Macro mode and patient images demonstrated the potential benefit of these scan modes for clinical practice.

Dual energy CT (DECT) measures the object of interest using two different x-ray spectra in order to provide energy-selective CT images or in order to get the material decomposition of the object. Today, two decomposition techniques are known. Image-based DECT uses linear combinations of reconstructed images to get an image that contains material-selective DECT information. Rawdata-based DECT correctly treats the available information by passing the rawdata through a decomposition function that uses information from both rawdata sets to create DECT specific (e.g., material-selective) rawdata. Then the image reconstruction yields material-selective images. Rawdata-based image decomposition generally obtains better image quality; however, it needs matched rawdata sets. This means that physically the same lines need to be measured for each spectrum. In today's CT scanners, this is not the case. The authors propose a new image-based method to combine mismatched rawdata sets for DECT information. The method allows for implementation in a scanner's rawdata precorrection pipeline or may be used in image domain. They compare the ability of the three methods (image-based standard method, proposed method, and rawdata-based standard method) to perform material decomposition and to provide monochromatic images. Thereby they use typical clinical and preclinical scanner arrangements including circular cone-beam CT and spiral CT. The proposed method is found to perform better than the image-based standard method and is inferior to the rawdata-based method. However, the proposed method can be used with the frequent case of mismatched data sets that exclude rawdata-based methods.

At matched CT scan protocol settings and identical image reconstruction parameters, the PCD yields superior in-stent lumen delineation of coronary artery stents as compared with conventional EID arrays.

The purpose of this study was to develop and evaluate the hybrid scatter correction algorithm (HSC) for CT imaging. Therefore, two established ways to perform scatter correction, i.e. physical scatter correction based on Monte Carlo simulations and a convolution-based scatter correction algorithm, were combined in order to perform an object-dependent, fast and accurate scatter correction. Based on a reconstructed CT volume, patient-specific scatter intensity is estimated by a coarse Monte Carlo simulation that uses a reduced amount of simulated photons in order to reduce the simulation time. To further speed up the Monte Carlo scatter estimation, scatter intensities are simulated only for a fraction of all projections. In a second step, the high noise estimate of the scatter intensity is used to calibrate the open parameters in a convolution-based algorithm which is then used to correct measured intensities for scatter. Furthermore, the scatter-corrected intensities are used in order to reconstruct a scatter-corrected CT volume data set. To evaluate the scatter reduction potential of HSC, we conducted simulations in a clinical CT geometry and measurements with a flat detector CT system. In the simulation study, HSC-corrected images were compared to scatter-free reference images. For the measurements, no scatter-free reference image was available. Therefore, we used an image corrected with a low-noise Monte Carlo simulation as a reference. The results show that the HSC can significantly reduce scatter artifacts. Compared to the reference images, the error due to scatter artifacts decreased from 100% for uncorrected images to a value below 20% for HSC-corrected images for both the clinical (simulated data) and the flat detector CT geometry (measurement). Compared to a low-noise Monte Carlo simulation, with the HSC the number of photon histories can be reduced by about a factor of 100 per projection without losing correction accuracy. Furthermore, it was sufficient to calibrate the parameters in the convolution model at an angular increment of about 20°. The reduction of the simulated photon histories together with the reduced amount of simulated Monte Carlo scatter projections decreased the total runtime of the scatter correction by about two orders of magnitude for the cases investigated here when using the HSC instead of a low-noise Monte Carlo simulation for scatter correction.

A dedicated sharp convolution kernel for PCD CT imaging of coronary stents yields superior qualitative and quantitative image characteristics compared with conventional reconstruction kernels. Resulting higher noise levels in sharp kernel PCD imaging can be partially compensated with iterative image reconstruction techniques.

No abstract

In this work, we introduce polarimetric balanced detection as a new attenuated total reflection (ATR) infrared (IR) sensing scheme, leveraging unequal effective thicknesses achieved with laser light of different polarizations. We combined a monolithic widely tunable Vernier quantum cascade laser (QCL-XT) and a multibounce ATR IR spectroscopy setup for analysis of liquids in a process analytical setting. Polarimetric balanced detection enables simultaneous recording of background and sample spectra, significantly reducing long-term drifts. The root-mean-square noise could be improved by a factor of 10 in a long-term experiment, compared to conventional absorbance measurements obtained via the single-ended optical channel. The sensing performance of the device was further evaluated by on-site measurements of ethanol in water, leading to an improved limit of detection (LOD) achieved with polarimetric balanced detection. Sequential injection analysis was employed for automated injection of samples into a custom-built ATR flow cell mounted above a zinc sulfide multibounce ATR element. The QCL-XT posed to be suitable for mid-IR-based sensing in liquids due to its wide tunability. Polarimetric balanced detection proved to enhance the robustness and long-term stability of the sensing device, along with improving the LOD by a factor of 5. This demonstrates the potential for new polarimetric QCL-based ATR mid-IR sensing schemes for in-field measurements or process monitoring usually prone to a multitude of interferences.

In absorption spectroscopy, infrared spectra of heated gases or condensed samples in the vapor phase are usually recorded with a single pass heated gas cell. This device exhibits two orders of magnitude lower sensitivity than the high-temperature multipass cell presented in this article. Our device is a novel type of compact long path absorption cell that can withstand aggressive chemicals in addition to temperatures up to 723 K. The construction of the cell and its technical features are described in detail, paying special attention to the mechanisms that compensate for thermal expansion and that allow the user to vary the optical path length under any thermal or vacuum condition. The cell may be used with a laser source or implemented within a Fourier transform infrared spectrometer. Its design is compatible with optical arrangements using astigmatic mirrors or spherical mirrors in a Herriott configuration. Here we implement a homebuilt Herriott-type cell with a total optical path length of up to 35 m. In order to demonstrate the feasibility of the cell, methane and water vapor absorption lines showing dissimilar temperature effects on line intensity were recorded with the help of a mid-infrared laser source tunable between 3 and 4 microm. Emphasis is put on lines that are too weak to be recorded with a single pass cell.