Interpolation Of Raw Data Research Articles

Reducing windmill artifacts in clinical spiral CT using a deep learning-based projection raw data upsampling: Method and robustness evaluation.

Multislice spiral computed tomography (MSCT) requires an interpolation between adjacent detector rows during backprojection. Not satisfying the Nyquist sampling condition along the z-axis results in aliasing effects, also known as windmill artifacts. These image distortions are characterized by bright streaks diverging from high contraststructures. The z-flying focal spot (zFFS) is a well-established hardware-based solution that aims to double the sampling rate in longitudinal direction and therefore reduce aliasing artifacts. However, given the technical complexity of the zFFS, this work proposes a deep learning-based approach as an alternativesolution. We propose a supervised learning approach to perform a mapping between input projections and the corresponding rows required for double sampling in the z-direction. We present a comprehensive evaluation using both a clinical dataset obtained using raw data from 40 real patient scans acquired with zFFS and a synthetic dataset consisting of 100 simulated spiral scans using a phantom specifically designed for our problem. For the clinical dataset, we utilized 32 scans as training set and 8 scans as validation set, whereas for the synthetic dataset, we used 80 scans for training and 20 scans for validation purposes. Both qualitative and quantitative assessments are conducted on a test set consisting of nine real patient scans and six phantom measurements to validate the performance of our approach. A simulation study was performed to investigate the robustness against different scan configurations in terms of detector collimation and pitchvalue. In the quantitative comparison based on clinical patient scans from the test set, all network configurations show an improvement in the root mean square error (RMSE) of approximately 20% compared to neglecting the doubled longitudinal sampling by the zFFS. The results of the qualitative analysis indicate that both clinical and synthetic training data can reduce windmill artifacts through the application of a correspondingly trained network. Together with the qualitative results from the test set phantom measurements it is emphasized that a training of our method with synthetic data resulted in superior performance in windmill artifactreduction. Deep learning-based raw data interpolation has the potential to enhance the sampling in z-direction and thus minimize aliasing effects, as it is the case with the zFFS. Especially a training with synthetic data showed promising results. While it may not outperform zFFS, our method represents a beneficial solution for CT scanners lacking the necessary hardware components forzFFS.

A comparison framework for temporal image reconstructions in electrical impedance tomography

Electrical impedance tomography (EIT) provides low-resolution images of internal conductivity distributions, but is able to achieve relatively high temporal resolutions. Most EIT image reconstruction algorithms do not explicitly account for the temporal constraints on the measurements or physiological processes under investigation. Instead, algorithms typically assume both that the conductivity distribution does not change during the acquisition of each EIT data frame, and that frames can be reconstructed independently, without consideration of the correlation between images. A failure to account for these temporal effects will result in aliasing-related artefacts in images. Several methods have been proposed to compensate for these effects, including interpolation of raw data, and reconstruction algorithms using Kalman and temporal filtering. However, no systematic work has been performed to understand the severity of the temporal artefacts nor the extent to which algorithms can account for them. We seek to address this need by developing a temporal comparison framework and figures of merit to assess the ability of reconstruction algorithms to account for temporal effects. Using this approach, we compare combinations of three reconstruction algorithms using three EIT data frame types: perfect, realistic and interpolated. The results show that, without accounting for temporal effects, artefacts are present in images for dynamic conductivity contrasts at frequencies 10–20 times slower than the frame rate. The proposed methods show some improvements in reducing these artefacts.

Finite element analysis of two total knee joint prostheses

Aim of this work is to compare two different total knee prostheses that differ mainly in the shape of the polyethylene (PE) component inserted between the femoral and tibial plates. The best solution between them has been originally reshaped in order to reduce stress peaks. The study procedure has been divided into the following steps. First step is the digitalisation of the shape of the prostheses by means of a 3D laser scanner. The morphology of two prototypes of the prostheses has been acquired by elaborating multiple Moire fringe patterns projected on their surfaces. Second step consisted on the manipulation of these data in a CAD module, that is the interpolation of raw data into NURBS surfaces, reducing singularities due to the typical scattering of the acquiring system. Third step has been the setting up of FEM simulations to evaluate the prostheses behaviour under benchmark loading conditions given in literature. The CAD model of the prostheses has been meshed into solid finite elements. Different flexion angles configurations have been analysed, the load being applied along the femoral axis. FEM analyses have returned stress fields in the PE insert and, in particular, in the stabilizing cam which function is to avoid dislocation. Last step has been the integrated use of CAD and FEM to modify the shape of the stabilizing cam of the best prosthesis, in order to reduce the stress peaks in the original prosthesis without affecting kinematics of the joint. Good results have been obtained both in terms of stress and contact pressure peaks reduction.

The effect of pitch in multislice spiral/helical CT.

The purpose of this study is to understand the effect of pitch on raw data interpolation in multislice spiral/helical computed tomography (CT) and provide guidelines for scanner design and protocol optimization. Multislice spiral CT is mainly characterized by the three parameters: the number of detector arrays, the detector collimation, and the table increment per x-ray source rotation. The pitch in multislice spiral CT is defined as the ratio of the table increment over the detector collimation in this study. In parallel to the current framework for studying longitudinal image resolution, the central fan-beam rays of direct and opposite directions are considered, assuming a narrow cone-beam angle. Generally speaking, sampling in the Radon domain by the direct and opposite central rays is nonuniform along the longitudinal axis. Using a recently developed methodology for quantifying the sensitivity of signal reconstruction from nonuniformly sampled finite points, the effect of pitch on raw data interpolation is analyzed in multislice spiral CT. Unlike single-slice spiral CT, in which image quality decreases monotonically as the pitch increases, the sensitivity of raw data interpolation in multislice spiral CT increases in an alternating way as the pitch increases, suggesting that image quality does not decrease monotonically in this case. The most favorable pitch can be found from the sensitivity-pitch plot for any given set of multislice spiral CT parameters. An example for four-slice spiral CT is provided. The study on the effect of pitch using the sensitivity analysis approach reveals the fundamental characteristics of raw data interpolation in multislice spiral CT, and gives insights into interaction between pitch and image quality. These results may be valuable for design of multislice spiral CT scanners and imaging protocol optimization in clinical applications.

Intrinsic activity and EC 50: the simplest tools for the evaluation of the dissociation constant of a partial agonist

In functional pharmacology, the Furchgott’s analysis and the Waud’s analysis are the most widely used among the reliable different methods actually available, for the determination of the dissociation constant of partial agonists. However, they need the application of relatively complicated procedures of manipulation and interpolation of raw data. On the basis of empirical assumptions, this article proposes a new approach, which probably can be considered the simplest method to determine the dissociation constant of a partial agonist, because of the rapid experimental protocol and the easy calculation procedure. Computer-generated concentration–response curves (CRC) for hypothesised partial agonists were analysed by the widely known Waud’s analysis and by this new approach. Furthermore, this new analysis was also used to evaluate experimental data from literature, relative to the dissociation constants of α-adrenoceptor partial agonists, recorded in rabbit and rat aortae and calculated by the Waud’s method. The results obtained by the new approach, both for the computer-generated and for the experimentally studied partial agonists, showed a high level of accuracy, when compared with the classical Waud’s analysis.

Optimal pitch in spiral computed tomography.

The focus of this paper is to analytically optimize spiral/helical computed tomography (CT) protocols based on a simplified imaging model. Spiral CT was approximately modeled as follows: Using the half-scan raw data interpolation method, the variance of the spiral CT slice sensitivity profile is equal to the sum of squared detector collimation divided by 12 and squared table increment divided by 24. Image noise variance is inversely proportional to tube current and detector collimation. The maximum continuous scanning time is inversely proportional to tube current. Slice thickness, image noise, and signal-to-noise ratio were, respectively, optimized for a given scanning coverage, consistently resulting in pitch of square root of 2. To avoid longitudinal aliasing, at least 2-3 transverse slices should be reconstructed per collimation. When the simplified spiral CT model is valid and a scanning range specified, 1.4 pitch is required for optimal image quality. The method can be applied to more accurate spiral CT models.

Blood flow measurement using variable velocity encoding in the RR interval

Velocity-encoded phase imaging using asynchronous gating requires input of a velocity encoding value to set the velocity sensitivity of the pulse sequence. The raw data interpolation and reconstruction scheme that the pulse sequence uses forces the encoding value to be constant throughout the RR interval. The sequence and the raw data interpolation scheme were modified to allow two velocity encodings during the RR interval. Two-hundred cm/s encoding was used in systole, and 30 cm/s in diastole. Changing the encoding in diastole significantly improved the accuracy and precision of ascending aorta flow measurements.

Comparison between retrospective gating and ECG triggering in magnetic resonance velocity mapping

ECG-triggered cinematographic studies of the cardiovascular system are hampered by several technical restrictions such as the inability to image end-diastole, ghosting, varying signal intensity, and phase contributions from eddy currents. Retrospective gating may solve these problems, but involves signal manipulation such as interpolating raw data from a time window. In this study, the performance of the two gating strategies was compared in quantitative MR velocity mapping on the abdominal aorta in eight healthy volunteers and on a pulsatile flow phantom. The results were compared to a one-dimensional velocity mapping technique and Doppler ultrasound. Finally, the consequence of decreasing the time window in the raw data interpolation used for retrospective gating was also examined. With retrospective gating, a low-pass filtering was seen, causing significantly prolonged duration and decreased amplitude of flow pulses. However, by reducing the time window retrospectively gated flow measurements were in good agreement with those that are ECG triggered. When fulfilling the demand of a narrow time window for interpolation, retrospective gating offers several advantages in MR velocity mapping.