MATLAB-based Software Package Research Articles

Exploration of the pulse pileup effects in a clinical CdTe-based photon-counting computed tomography.

High tube current generates a high flux of x-rays to photon counting detectors (PCDs) that can potentially result in the piling up of pulses formed by concurrent photons, which can cause count loss and energy resolution degradation. To evaluate the performance of clinical photon-counting CT (PCCT) systems in high flux, potentially influenced by pulse pileup effects, in terms of task-generic image quality metrics. A clinical phantom was scanned on a commercial PCCT scanner (NAEOTOM Alpha, Siemens) at 120kV under fourteen different tube current levels (40-1000mA) with a rotation time of 0.25 s and a pitch of 1. The dose levels corresponded to CTDIvol (32cm phantom) of 0.79-19.8mGy. CT sinograms were reconstructed using QIR-off mode (noniterative reconstruction algorithm), Br44 kernel, and a voxel size of . imQuest, an open-source MATLAB-based software package was used to calculate noise power spectrum (NPS), task transfer function (TTF), contrast-to-noise ratio (CNR), and CT number according to AAPM Task Group 233 metrology. The 50% cut-off frequency of TTF (f50 ) remained mostly constant across all higher tube currents for all inserts, namely polyethylene, bone, air, and acrylic. Using the lowest two data points (40 and 80mA), the expected relationship between noise magnitude and tube current was determined to be noise mA-0.47 . The measured noise magnitude were up to 11.1% higher than the expected value at the highest tube current. The average frequency of NPS (fav ) decreased from 0.32 to 0.29mm-1 as tube current increased from 40 to 1000mA. No considerable effects were observed in CT number measurement of any insert; however, CT numbers for air and bone changed almost monotonically as tube current increased. Absolute CNR increased monotonically for all inserts; however, the difference between measured and expected CNRs were approximately -6% to 12% across all tube currents. Increasing tube currents did not affect the spatial resolution, but slightly affected the CT number and noise measurements of the clinical PCCT system. However, the effects were only considerable at clinically irrelevant tube currents used on a small 20-cm phantom. In general clinical practices, automatic exposure control techniques are used to decrease the variation of flux on the detector, which alleviates the chances of detector saturation due to high count rates. The observed effects could be due to pulse pileup, signal-dependent filtration of the system, or nonlinearities in the reconstruction algorithm. In conclusion, either the deadtime of the detector used in the photon-counting CT system is shorter such that count losses due to pulse pileup are negligible, or pulse pileup has inconsiderable effects on the image quality of clinical photon-counting CT systems in routine clinical practice due to possible corrections applied on the system.

PATLAB: A graphical computational software package for photoacoustic computed tomography research

Photoacoustic tomography (PAT) provides high resolution optical images of tissue at depths of up to several centimetres. This modality has been of interest to researchers for at least 30 years and is still the subject of intensive research. However, PAT researchers lack access to a comprehensive open-source graphical simulation and reconstruction software package. In this article, we introduce PATLAB, an open-source MATLAB-based graphical software package that can perform both PAT simulation and image reconstruction. PATLAB is simple to use yet is capable of complex PAT data processing tasks and offers advanced users a framework to build and test new methods.

The Adaptive Dynamic Programming Toolbox.

The paper develops the adaptive dynamic programming toolbox (ADPT), which is a MATLAB-based software package and computationally solves optimal control problems for continuous-time control-affine systems. The ADPT produces approximate optimal feedback controls by employing the adaptive dynamic programming technique and solving the Hamilton–Jacobi–Bellman equation approximately. A novel implementation method is derived to optimize the memory consumption by the ADPT throughout its execution. The ADPT supports two working modes: model-based mode and model-free mode. In the former mode, the ADPT computes optimal feedback controls provided the system dynamics. In the latter mode, optimal feedback controls are generated from the measurements of system trajectories, without the requirement of knowledge of the system model. Multiple setting options are provided in the ADPT, such that various customized circumstances can be accommodated. Compared to other popular software toolboxes for optimal control, the ADPT features computational precision and time efficiency, which is illustrated with its applications to a highly non-linear satellite attitude control problem.

Simultaneous measurement of acoustic pressure and temperature at the focus of high intensity focused ultrasound in a tissue-mimicking phantom by using a fiber-optic hydrophone

The simultaneous measurement of the acoustic pressure and the temperature at the focus of high intensity focused ultrasound (HIFU) in a tissue-mimicking phantom were performed by using a dual sensing fiber-optic hydrophone (FOH). The HIFU pressure and the HIFU-induced temperature rise at the focus in the phantom were numerically simulated by using a MATLAB-based software package developed for HIFU simulation. The measurements of the HIFU-induced temperature rise showed good agreement with the simulations. It was also found that the presence of the FOH tip at the focus in the phantom did not affect the formation of a thermal lesion.

IA-Lab: A MATLAB framework for efficient microscopy image analysis development, applied to quantifying intracellular transport of internalized peptide-drug conjugate.

This work presents a MATLAB-based software package for high-throughput microscopy image analysis development, making such development more accessible for a large user community. The toolbox provides a GUI and a number of analysis workflows, and can serve as a general framework designed to allow for easy extension. For a new application, only a minor part of the object-oriented code needs to be replaced by new components, making development efficient. This makes it possible to quickly develop solutions for analysis not available in existing tools. We show its use in making a tool for quantifying intracellular transport of internalized peptide-drug conjugates.The code is freely available as open source on GitHub (https://github.com/amcorrigan/ia-lab)

COMPASS: An Open-Source, General-Purpose Software Toolkit for Computational Psychiatry

Mathematical modeling of behavior during a psychophysical task, referred to as “computational psychiatry,” could greatly improve our understanding of mental disorders. One barrier to the broader adoption of computational methods, is that they often require advanced statistical modeling and mathematical skills. Biological and behavioral signals often show skewed or non-Gaussian distributions, and very few toolboxes and analytical platforms are capable of processing such signal categories. We developed the Computational Psychiatry Adaptive State-Space (COMPASS) toolbox, an open-source MATLAB-based software package. This toolbox is easy to use and capable of integrating signals with a variety of distributions. COMPASS has the tools to process signals with continuous-valued and binary measurements, or signals with incomplete—missing or censored—measurements, which makes it well-suited for processing those signals captured during a psychophysical task. After specifying a few parameters in a small set of user-friendly functions, COMPASS allows users to efficiently apply a wide range of computational behavioral models. The model output can be analyzed as an experimental outcome or used as a regressor for neural data and can also be tested using the goodness-of-fit measurement. Here, we demonstrate that COMPASS can replicate two computational behavioral analyses from different groups. COMPASS replicates and can slightly improve on the original modeling results. We also demonstrate the use of COMPASS application in a censored-data problem and compare its performance result with naïve estimation methods. This flexible, general-purpose toolkit should accelerate the use of computational modeling in psychiatric neuroscience.

An open-source tool for analysis and automatic identification of dendritic spines using machine learning.

Synaptic plasticity, the cellular basis for learning and memory, is mediated by a complex biochemical network of signaling proteins. These proteins are compartmentalized in dendritic spines, the tiny, bulbous, post-synaptic structures found on neuronal dendrites. The ability to screen a high number of molecular targets for their effect on dendritic spine structural plasticity will require a high-throughput imaging system capable of stimulating and monitoring hundreds of dendritic spines in various conditions. For this purpose, we present a program capable of automatically identifying dendritic spines in live, fluorescent tissue. Our software relies on a machine learning approach to minimize any need for parameter tuning from the user. Custom thresholding and binarization functions serve to “clean” fluorescent images, and a neural network is trained using features based on the relative shape of the spine perimeter and its corresponding dendritic backbone. Our algorithm is rapid, flexible, has over 90% accuracy in spine detection, and bundled with our user-friendly, open-source, MATLAB-based software package for spine analysis.

Prediction and Measurement of Temperature Rise Induced by High Intensity Focused Ultrasound in a Tissue-Mimicking Phantom

The present study aims to predict the temperature rise induced by high intensity focused ultrasound (HIFU) in soft tissues to assess tissue damage during HIFU thermal therapies. With the help of a MATLAB-based software package developed for HIFU simulation, the HIFU field was simulated by solving the axisymmetric Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation from the frequency-domain perspective, and the HIFU-induced temperature rise in a tissue-mimicking phantom was simulated by solving Pennes’ bioheat transfer (BHT) equation. In order to verify the simulation results, we performed in-vitro heating experiments on a tissue-mimicking phantom by using a 1.1-MHz, single-element, spherically focused HIFU transducer. The temperature rise near the focal spot obtained from the HIFU simulator was in good agreement with that from the in-vitro experiments. This confirms that the HIFU simulator based on the KZK and the BHT equations captures the HIFU-induced temperature rise in soft tissues well enough to make it suitable for HIFU treatment planning.

Linear Control Toolbox - supporting B-splines in LPV control

This paper presents the Linear Control Toolbox, a freely available Matlab-based software package primarily focused on optimal feedback controller design for LTI and LPV systems. Its main goal is to make more involved controller design methodologies accessible to the broader public by providing tailored synthesis and analysis tools. The paper gives an overview of the different modules within the toolbox, the underlying data structures and the supported functionalities and algorithms. Moreover two case studies are elaborated. The autopilot of a missile serves as a comparison of the Linear Control Toolbox with its competitors and an overhead crane setup was used to demonstrate the use and experimentally validate the presented toolbox.

EXONEST: The Bayesian Exoplanetary Explorer

The fields of astronomy and astrophysics are currently engaged in an unprecedented era of discovery as recent missions have revealed thousands of exoplanets orbiting other stars. While the Kepler Space Telescope mission has enabled most of these exoplanets to be detected by identifying transiting events, exoplanets often exhibit additional photometric effects that can be used to improve the characterization of exoplanets. The EXONEST Exoplanetary Explorer is a Bayesian exoplanet inference engine based on nested sampling and originally designed to analyze archived Kepler Space Telescope and CoRoT (Convection Rotation et Transits planétaires) exoplanet mission data. We discuss the EXONEST software package and describe how it accommodates plug-and-play models of exoplanet-associated photometric effects for the purpose of exoplanet detection, characterization and scientific hypothesis testing. The current suite of models allows for both circular and eccentric orbits in conjunction with photometric effects, such as the primary transit and secondary eclipse, reflected light, thermal emissions, ellipsoidal variations, Doppler beaming and superrotation. We discuss our new efforts to expand the capabilities of the software to include more subtle photometric effects involving reflected and refracted light. We discuss the EXONEST inference engine design and introduce our plans to port the current MATLAB-based EXONEST software package over to the next generation Exoplanetary Explorer, which will be a Python-based open source project with the capability to employ third-party plug-and-play models of exoplanet-related photometric effects.

Investigation of thermomechanical motion in a nanomechanical resonator based on optical intensity mapping

In the present study, the acoustic field of a high intensity focused ultrasound (HIFU) transducer in water was measured by using a commercially available needle hydrophone intended for HIFU use. To validate the results of hydrophone measurements, numerical simulations of HIFU fields were performed by integrating the axisymmetric Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation from the frequency-domain perspective with the help of a MATLAB-based software package developed for HIFU simulation. Quantitative values for the focal waveforms, the peak pressures, and the size of the focal spot were obtained in various regimes of linear, quasilinear, and nonlinear propagation up to the source pressure levels when the shock front was formed in the waveform. The numerical results with the HIFU simulator solving the KZK equation were compared with the experimental data and found to be in good agreement. This confirms that the numerical simulation based on the KZK equation is capable of capturing the nonlinear pressure field of therapeutic HIFU transducers well enough to make it suitable for HIFU treatment planning.

Quantitative analysis of total reflection X-ray fluorescence from finely layered structures using XeRay.

Total reflection x-ray fluorescence (TXRF) is a widely applicable experimental technique for studying chemical element distributions across finely layered structures at extremely high sensitivity. To promote and facilitate scientific discovery using TXRF, we developed a MATLAB-based software package with a graphical user interface, named XeRay, for quick, accurate, and intuitive data analysis. XeRay lets the user model any layered system, each layer with its independent chemical composition and thickness, and enables fine-tuned data fitting. The accuracy of XeRay has been tested in the analysis of TXRF data from both air/liquid interface and liquid/liquid interfacial studies and has been compared to literature results. In an air/liquid interface study, Ca2+ sequestration was measured at a Langmuir monolayer of 1-stearoyl-2-oleoyl-sn-glycero-3-phosphatidic acid (SOPA) on a buffer solution of 1 mM CaCl2 at pH 7.5. Data analysis with XeRay reveals that each 1 nm2 of interfacial area contains 2.38 ± 0.06 Ca2+ ions, which corresponds to a 1:1 ratio between SOPA headgroups and Ca2+ ions, consistent with several earlier reports. For the liquid/liquid interface study of Sr2+ enrichment at the dodecane/surfactant/water interface, analysis using XeRay gives a surface enrichment of Sr2+ at 68-5+6 Å2 per ion, consistent with the result published for the same dataset.

EPV 5. Tractography of hippocampal association fibers in patients with hippocampal sclerosis and temporal lobe epilepsy

Introduction Temporal lobe epilepsy (TLE) is the most common focal epilepsy and is often caused by hippocampal sclerosis (HS) ( Babb and Brown, 1987 ). As the hippocampal formation is an essential part of the Papez circuit, we investigated whether HS is associated with alterations of the Papez circuit network. The aim of our study was to analyse alterations of fibers connecting the affected hippocampus by applying a new Diffusion-weighted MRI (DTI) method called “Global Tracking”. Methods Whole brain “Global Tracking” based on high-angular diffusion weighted imaging in 61 directions was performed on a 3 Tesla MRI scanner in 20 TLE-patients with unilateral ( n  = 17) and bilateral ( n  = 3) hippocampal sclerosis as well as in 20 healthy controls individually matched for age, gender and handedness as reference group. The fiber tracts of interest, i.e. whole cingulum and the hippocampus-associated part of the cingulum, respectively, were selected on color coded DTI images superimposed on a T1w 3D sequence. The fiber tracts were selected on color coded Fractional Anisotropy (FA) maps using a MATLAB-based software package FiberViewerTool ( Reisert et al., 2011 ) ( Fig. 1 ). From these individually derived tracts the numbers of streamlines were extracted and statistically evaluated using paired Wilcoxon signed rank tests. Results Streamline counts of fibers between pathologically altered hippocampal structures and the whole cingulate gyrus (cgc; p  = 0.000021) and the hippocampus-associated tract of the cingulate gyrus (chc; p  = 0.00054), respectively, were significantly lower in patients than in the corresponding hemisphere of individually matched healthy controls (Figs. 3 and 4). The same was true when comparing the corresponding fibers (cgc: p  = 0.0021/chc: p  = 0.00098) in the hemisphere contralateral to the hippocampal pathology in patients and controls (Figs. 5 and 6) Conclusion The ability to delineate the substructures of the Papez circuit offers the basis for monitoring structural white matter changes in patients with HS. Our results support the notion that we have to consider focal lesions like HS in the CNS in the context of larger alterations in the whole intracerebral network.

MATtrack: A MATLAB-Based Quantitative Image Analysis Platform for Investigating Real-Time Photo-Converted Fluorescent Signals in Live Cells.

We introduce here MATtrack, an open source MATLAB-based computational platform developed to process multi-Tiff files produced by a photo-conversion time lapse protocol for live cell fluorescent microscopy. MATtrack automatically performs a series of steps required for image processing, including extraction and import of numerical values from Multi-Tiff files, red/green image classification using gating parameters, noise filtering, background extraction, contrast stretching and temporal smoothing. MATtrack also integrates a series of algorithms for quantitative image analysis enabling the construction of mean and standard deviation images, clustering and classification of subcellular regions and injection point approximation. In addition, MATtrack features a simple user interface, which enables monitoring of Fluorescent Signal Intensity in multiple Regions of Interest, over time. The latter encapsulates a region growing method to automatically delineate the contours of Regions of Interest selected by the user, and performs background and regional Average Fluorescence Tracking, and automatic plotting. Finally, MATtrack computes convenient visualization and exploration tools including a migration map, which provides an overview of the protein intracellular trajectories and accumulation areas. In conclusion, MATtrack is an open source MATLAB-based software package tailored to facilitate the analysis and visualization of large data files derived from real-time live cell fluorescent microscopy using photoconvertible proteins. It is flexible, user friendly, compatible with Windows, Mac, and Linux, and a wide range of data acquisition software. MATtrack is freely available for download at eleceng.dit.ie/courtney/MATtrack.zip.

Interpretation of gravity anomalies to delineate some structural features of Biga and Gelibolu peninsulas, and their surroundings (north-west Turkey)

On the basis of gravity data, derived anomaly traces were presented for the interpretation of some shallow structural features of Biga and Gelibolu peninsulas. Since building general understanding of subtle details about subsurface geology is of great importance considering that the study area is tectonically important, some advanced data processing techniques were implemented to gravity anomalies in a detailed manner. The procedures were performed using a MATLAB-based software package (Gravity and Magnetic Interpretation – GMINTERP). First, a finite element method was utilised to produce the residual data-set which is expected to reflect short wavelength anomalies arising from shallower geological structures, and thereafter some derivative-based algorithms were executed to analyse the residual data. The general anomaly patterns obtained from the applications clearly corresponded to the well-known surface geology map of the study area. Derivative-based anomaly maps put forward some findings about the existence of an old caldera structure in the western part of the Biga Peninsula. Additionally, abrupt lateral changes in anomaly amplitudes indicated the presence of some major structural discontinuities. Thus, findings yielded to make significant geological interpretations that might be important for further investigations. This study also showed that GMINTERP software package proved useful in assisting geological interpretation using geophysical potential field data-sets.

Determination of the local tie vector between the VLBI and GNSS reference points at Onsala using GPS measurements

Two gimbal-mounted GNSS antennas were installed on each side of the radome-enclosed 20 m VLBI radio telescope at the Onsala Space Observatory. GPS data with a 1 Hz sampling rate were recorded for five semi-kinematic and four kinematic observing campaigns. These GPS data were analysed together with data from the IGS station ONSA with an in-house Matlab-based GPS software package, using the double-difference analysis strategy. The coordinates of the GNSS antennas on the telescope were estimated for different observation angles of the telescope, at specific epochs, and used to calculate the geodetic reference point of the telescope. The local tie vector between the VLBI and the ONSA GNSS reference points in a geocentric reference frame was hence obtained. The two different types of observing campaigns gave consistent results of the estimated local tie vector and the axis offset of the telescope. The estimated local tie vector obtained from all nine campaigns gave standard deviations of 1.5, 1.0, and 2.9 mm for the geocentric X, Y, and Z components, respectively. The result of the estimated axis offset of the VLBI telescope shows a difference of 0.3 mm, with a standard deviation of 1.9 mm, with respect to a reference value obtained by two local surveys carried out in 2002 and 2008. Our results show that the presented method can be used as a complement to the more accurate but more labour intensive classical geodetic surveys to continuously monitor the local tie at co-location stations with an accuracy of a few millimetres.

Generalized Isotonic Regression

We present a new computational and statistical approach for fitting isotonic models under convex differentiable loss functions through recursive partitioning. Models along the partitioning path are also isotonic and can be viewed as regularized solutions to the problem. Our approach generalizes and subsumes the well-known work of Barlow and Brunk on fitting isotonic regressions subject to specially structured loss functions, and expands the range of loss functions that can be used (e.g., adding Huber loss for robust regression). This is accomplished through an algorithmic adjustment to a recursive partitioning approach recently developed for solving large-scale ł2-loss isotonic regression problems. We prove that the new algorithm solves the generalized problem while maintaining the favorable computational and statistical properties of the l2 algorithm. The results are demonstrated on both real and synthetic data in two settings: fitting count data using negative Poisson log-likelihood loss, and fitting robust isotonic regressions using Huber loss. Proofs of theorems and a MATLAB-based software package implementing our algorithm are available in the online supplementary materials.

SU‐E‐I‐99: Demonstration the Capability of X‐Ray Frequency Modulation Imaging Technique Under Noisy Environment

Purpose: Frequency modulation technique has been proposed for x‐ray imaging applications due to the recent development of carbon nanotube (CNT) field emission based x‐ray source technology, which is capable of modulating x‐ray radiation waveforms with different frequencies. The purpose of this work is to evaluate the performance of x‐ray frequency modulation imaging technique especially under noisy radioactive environment. Methods: A dedicated Matlab based software package written in house was used to simulate and evaluate the imaging performance of x‐ray frequency modulation imaging technique. A full scale imaging system was modeled for our simulation purpose. An x‐ray tube with the capability of generating pulsed x‐ray waveforms with different modulation frequencies was used as the x‐ray source. A simple cylindrical object was used as the imaging object. Random noise signal was added in to simulate the background radiation noise. And a high‐speed flat panel x‐ray camera was used to record the x‐ray radiation signal transmitted through the object. The final image was synthesized by decoding the recorded x‐ray signal based on a Fourier transform based algorithm. Results: Based on the simulation results, the new x‐ray frequency modulation imaging technique has dramatically enhanced the imaging quality by filtering out the background noise as indicated by the improved SNR values. Similar Result was also achieved by applying the same technique on a more realistic human chest x‐ray imaging application. Conclusion: In this paper we have reported some simulation results on the assessment of imaging performance of the novel x‐ray frequency modulation imaging technique under different noise environments. Our results showed that under appropriate imaging conditions, x‐ray frequency modulation imaging technique has the potential to greatly improve the imaging quality under noisy radioactive environment. Once fully developed this imaging technique has its promising potential for a variety of imaging applications.

Quantitative damage evaluation of AAR-affected concrete by DIP technique

This paper presents a method to evaluate alkali–aggregate reaction (AAR) damage in concrete by digital-image-processing (DIP) technique. A vacuum fluorescent-epoxy impregnation technique is used to highlight microcracks in the AAR-damaged concrete and a Matlab-based software package is developed to quantitatively analyse the microcrack characteristics (area, length, width etc.) in the fluorescent microscopic images of concrete. Six microcrack pattern parameters – the total length, the length density, the total area, the area density, the maximum width and the average width of microcracks – in slices from the concrete specimens that suffered different degrees of AAR damage were obtained. Results show that the length density, the area density and the average/maximum width of microcracks all increase as the degree of AAR damage increases. Relationships between the mechanical properties and the microcrack characteristics are established and results show that both the relative flexural strength and relative axial tensile strength have quadratic correlations with the microcrack density. The degree of AAR damage has a good logarithmic correlation with the microcrack density and the expansion ratio has a linear correlation with the microcrack density. Quantitative microcrack analysis based on DIP techniques could be developed as a new powerful tool of quantifying AAR damage in concrete.

UNIT: A freely available system identification toolbox

This paper presents a Matlab-based software package for the estimation of dynamic systems. It has been developed primarily as a platform to support the objective evaluation of novel approaches relative to existing methods within a common software framework. This is designed to streamline comparisons. The work here provides an explanation of the toolbox's design and use together with an overview of the underlying supported models and algorithms. An application study involving a lightly damped resonant system and a simulation example involving two non-linear systems are also presented in order to illustrate the use and capabilities of the toolbox.