Concept: Reconstruction algorithm
The paper presents a multifunctional joint sensor with measurement adaptability for biological engineering applications, such as gait analysis, gesture recognition, etc. The adaptability is embodied in both static and dynamic environment measurements, both of body pose and in motion capture. Its multifunctional capabilities lay in its ability of simultaneous measurement of multiple degrees of freedom (MDOF) with a single sensor to reduce system complexity. The basic working mode enables 2DOF spatial angle measurement over big ranges and stands out for its applications on different joints of different individuals without recalibration. The optional advanced working mode enables an additional DOF measurement for various applications. By employing corrugated tube as the main body, the sensor is also characterized as flexible and wearable with less restraints. MDOF variations are converted to linear displacements of the sensing elements. The simple reconstruction algorithm and small outputs volume are capable of providing real-time angles and long-term monitoring. The performance assessment of the built prototype is promising enough to indicate the feasibility of the sensor.
Super-resolved structured illumination microscopy (SR-SIM) is an important tool for fluorescence microscopy. SR-SIM microscopes perform multiple image acquisitions with varying illumination patterns, and reconstruct them to a super-resolved image. In its most frequent, linear implementation, SR-SIM doubles the spatial resolution. The reconstruction is performed numerically on the acquired wide-field image data, and thus relies on a software implementation of specific SR-SIM image reconstruction algorithms. We present fairSIM, an easy-to-use plugin that provides SR-SIM reconstructions for a wide range of SR-SIM platforms directly within ImageJ. For research groups developing their own implementations of super-resolution structured illumination microscopy, fairSIM takes away the hurdle of generating yet another implementation of the reconstruction algorithm. For users of commercial microscopes, it offers an additional, in-depth analysis option for their data independent of specific operating systems. As a modular, open-source solution, fairSIM can easily be adapted, automated and extended as the field of SR-SIM progresses.
AIM: The aim of our study was to assess improvements in spatial resolution and noise control from the application of the Astonish resolution recovery algorithm for single photon emission computed tomography imaging. Secondary aims were to compare acquisitions made with low-energy general purpose collimators with those obtained using low-energy high-resolution collimators in this context and evaluate the potential of a finer matrix to improve image quality further. MATERIALS AND METHODS: A Tc-filled Jaszczak phantom with hot spheres was used to assess contrast and noise. A National Electrical Manufacturers Association triple line source single photon emission computed tomography resolution phantom was used to measure spatial resolution. Acquisitions were made using both low-energy high-resolution and low-energy general purpose collimators. RESULTS: Compared with standard ordered subsets expectation maximization reconstructions, the resolution recovery algorithm resulted in a higher spatial resolution (8 vs. 14 mm full-width at half-maximum) leading to reduced partial volume effects in the smaller Jaszczak spheres. Higher image contrast was achieved alongside lower levels of noise. An edge enhancement artefact was observed in the resolution recovery corrected images. An overestimate of the target-to-background activity was also observed for the larger spheres. CONCLUSION: The use of such an algorithm results in images characterized by increased spatial resolution and reduced noise. However, small sources of the order of 2-3 cm can be significantly overenhanced.
In this article, we demonstrate the application of a new compressed sensing three-dimensional reconstruction algorithm for electron tomography that increases the accuracy of morphological characterization of nanostructured materials such as nanocrystalline iron oxide particles. A powerful feature of the algorithm is an anisotropic total variation norm for the L1 minimization during algebraic reconstruction that effectively reduces the elongation artifacts caused by limited angle sampling during electron tomography. The algorithm provides faithful morphologies that have not been feasible with existing techniques.
- Journal of applied clinical medical physics / American College of Medical Physics
- Published almost 3 years ago
When patient anatomy is positioned away from a CT scanner’s isocenter, scans of limited diagnostic value may result. Yet in some cases, positioning of patient anatomy far from isocenter is unavoidable. This study examines the effect of posi-tion and reconstruction algorithm on image resolution achieved by a CT scanner operating in a high resolution (HR) scan mode which incorporates focal spot deflection and acquires an increased number of projections per rotation. Images of a metal bead contained in a phantom were acquired on a GE CT750 HD scanner with multiple reconstruction algorithms, in the normal and HR scan mode, and at two positions, scanner isocenter and 15 cm directly above isocenter. The images of the metal bead yielded two-dimensional point spread functions which were averaged along two perpendicular directions to yield line spread functions. Fourier transforms of the line spread functions yielded radial and azimuthal modulation transfer functions (MTFs). At isocenter, the radial and azimuthal MTFs were aver-aged. MTF improvement depended on image position and modulation direction. The results from a single algorithm, Edge, can be generalized to other algorithms. At isocenter, the 10% MTF cutoff was 14.4 cycles/cm in normal and HR mode. At 15 cm above isocenter, the 10% cutoff was 6.0 and 8.5 cycles/cm for the azimuthal and radial MTFs in normal mode. In HR mode, the azimuthal and radial MTF 10% cutoff was 8.3 and 10.3 cycles/cm. Our results indicate that the best image resolu-tion is achieved at scanner isocenter and that the azimuthal resolution degrades more significantly than the radial resolution. For the GE CT750 HD CT scanner, the resolution is significantly enhanced by the HR scan mode away from scanner isocenter, and the use of the HR scan mode has much more of an impact on image resolution away from isocenter than the choice of algorithm.
First clinical investigation of a 4D maximum likelihood reconstruction for 4D PET-based treatment verification in ion beam therapy
- Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
- Published almost 2 years ago
In clinical applications of Positron Emission Tomography (PET)-based treatment verification in ion beam therapy (PT-PET), detection and interpretation of inconsistencies between Measured PET and Expected PET are mostly limited by Measured PET noise, due to low count statistics, and by Expected PET bias, especially due to inaccurate washout modelling in off-line implementations. In this work, a recently proposed 4D Maximum Likelihood (ML) reconstruction algorithm which considers Measured PET and Expected PET as two different motion phases of a 4D dataset is assessed on clinical 4D PET-CT datasets acquired after carbon ion therapy.
The objective of this study was to quantify any improvement with the GE ‘Sharp IR’ point-spread function (PSF) reconstruction algorithm in addition to ordered subsets expectation maximum (OSEM) and time-of-flight (TOF) reconstruction algorithms and establish the optimum parameters to be used in clinical studies.
Cryo-electron tomography (cryo-ET) allows cellular ultrastructures and macromolecular complexes to be imaged in three-dimensions in their native environments. Cryo-electron tomograms are reconstructed from projection images taken at defined tilt-angles. In order to recover high-resolution information from cryo-electron tomograms, it is necessary to measure and correct for the contrast transfer function (CTF) of the microscope. Most commonly, this is performed using protocols that approximate the sample as a two-dimensional (2D) plane. This approximation accounts for differences in defocus and therefore CTF across the tilted sample. It does not account for differences in defocus of objects at different heights within the sample; instead, a 3D approach is required. Currently available approaches for 3D-CTF correction are computationally expensive and have not been widely implemented. Here we simulate the benefits of 3D-CTF correction for high-resolution subtomogram averaging, and present a user-friendly, computationally-efficient 3D-CTF correction tool, NovaCTF, that is compatible with standard tomogram reconstruction workflows in IMOD. We validate the approach on synthetic data and test it using subtomogram averaging of real data. Consistent with our simulations, we find that 3D-CTF correction allows high-resolution structures to be obtained with much smaller subtomogram averaging datasets than are required using 2D-CTF. We also show that using equivalent dataset sizes, 3D-CTF correction can be used to obtain higher-resolution structures. We present a 3.4 Å resolution structure determined by subtomogram averaging.
X-ray tomography is a well-established technique to characterize 3D structures in material sciences and biology; its magnetic analogue-magnetic X-ray tomography-is yet to be developed. Here we demonstrate the visualization and reconstruction of magnetic domain structures in a 3D curved magnetic thin films with tubular shape by means of full-field soft X-ray microscopies. The 3D arrangement of the magnetization is retrieved from a set of 2D projections by analysing the evolution of the magnetic contrast with varying projection angle. Using reconstruction algorithms to analyse the angular evolution of 2D projections provides quantitative information about domain patterns and magnetic coupling phenomena between windings of azimuthally and radially magnetized tubular objects. The present approach represents a first milestone towards visualizing magnetization textures of 3D curved thin films with virtually arbitrary shape.
This paper presents new data driven methods for the time of flight (TOF) calibration of positron emission tomography (PET) scanners. These methods are derived from the consistency condition for TOF PET, they can be applied to data measured with an arbitrary tracer distribution and are numerically efficient because they do not require a preliminary image reconstruction from the non-TOF data. Two-dimensional simulations are presented for one of the methods, which only involves the two first moments of the data with respect to the TOF variable. The numerical results show that this method estimates the detector timing offsets with errors that are larger than those obtained via an initial non-TOF reconstruction, but remain smaller than 10 % of the TOF resolution and thereby have a limited impact on the quantitative accuracy of the activity image estimated with standard maximum likelihood reconstruction algorithms.