Image Point Spread Function Research Articles

Edge Artifacts in Point Spread Function-based PET Reconstruction in Relation to Object Size and Reconstruction Parameters.

Objective(s):We evaluated edge artifacts in relation to phantom diameter and reconstruction parameters in point spread function (PSF)-based positron emission tomography (PET) image reconstruction.Methods:PET data were acquired from an original cone-shaped phantom filled with 18F solution (21.9 kBq/mL) for 10 min using a Biograph mCT scanner. The images were reconstructed using the baseline ordered subsets expectation maximization (OSEM) algorithm and the OSEM with PSF correction model. The reconstruction parameters included a pixel size of 1.0, 2.0, or 3.0 mm, 1-12 iterations, 24 subsets, and a full width at half maximum (FWHM) of the post-filter Gaussian filter of 1.0, 2.0, or 3.0 mm. We compared both the maximum recovery coefficient (RCmax) and the mean recovery coefficient (RCmean) in the phantom at different diameters.Results:The OSEM images had no edge artifacts, but the OSEM with PSF images had a dense edge delineating the hot phantom at diameters 10 mm or more and a dense spot at the center at diameters of 8 mm or less. The dense edge was clearly observed on images with a small pixel size, a Gaussian filter with a small FWHM, and a high number of iterations. At a phantom diameter of 6-7 mm, the RCmax for the OSEM and OSEM with PSF images was 60% and 140%, respectively (pixel size: 1.0 mm; FWHM of the Gaussian filter: 2.0 mm; iterations: 2). The RCmean of the OSEM with PSF images did not exceed 100%.Conclusion:PSF-based image reconstruction resulted in edge artifacts, the degree of which depends on the pixel size, number of iterations, FWHM of the Gaussian filter, and object size.

Unbiased Filtered Back-Projection in $4\pi$ Compton Imaging With 3D Position Sensitive Detectors

In Compton imaging, iterative methods provide good performance but are usually computationally intensive. Thus, direct inverse algorithms such as filtered back-projection (FBP) are preferable when computation time is limited. The conventional FBP method assumes that the point spread function of a back-projection image is isotropic and invariant to incident direction, as required by frequency spectrum analysis. However, most of the time this assumption is not true because the detector geometry is rarely uniform. Therefore the conventional FBP reconstructed image is biased. To solve the geometry non-uniformity problem, this paper proposes an unbiased FBP algorithm that groups Compton events having the same Compton rings using a system matrix decomposition strategy. The proposed method produces more isotropic resolution, and preserves the capability to use frequency spectrum analysis. The algorithm has been applied to data from a 3D position-sensitive detector array with 4 crystals and a digital readout system. The resulting images had more isotropic resolution than standard FBP.

COSMIC SHEAR MEASUREMENT USING AUTO-CONVOLVED IMAGES

ABSTRACT We study the possibility of using quadrupole moments of auto-convolved galaxy images to measure cosmic shear. The autoconvolution of an image corresponds to the inverse Fourier transformation of its power spectrum. The new method has the following advantages: the smearing effect due to the point-spread function (PSF) can be corrected by subtracting the quadrupole moments of the auto-convolved PSF; the centroid of the auto-convolved image is trivially identified; the systematic error due to noise can be directly removed in Fourier space; the PSF image can also contain noise, the effect of which can be similarly removed. With a large ensemble of simulated galaxy images, we show that the new method can reach a sub-percent level accuracy under general conditions, albeit with increasingly large stamp size for galaxies of less compact profiles.

Quantifying intraocular scatter with near diffraction-limited double-pass point spread function.

Measurement of the double-pass (DP) point-spread function (PSF) can provide an objective and non-invasive method for estimating intraocular scatter in the human eye. The objective scatter index (OSI), which is calculated from the DP PSF images, is commonly used to quantify intraocular scatter. In this article, we simulated the effect of higher-order ocular aberrations on OSI, and the results showed that higher-order ocular aberrations had a significant influence on OSI. Then we developed an adaptive optics DP PSF measurement system (AO-DPPMS) which was capable of correcting ocular aberrations up to eighth-order radial Zernike modes over a 6.0-mm pupil. Employing this system, we obtained DP PSF images of four subjects at the fovea. OSI values with aberrations corrected up to 2nd, 5th and 8th Zernike order were calculated respectively, from the DP PSF images of the four subjects. The experimental results were consistent with the simulation, suggesting that it is necessary to compensate for the higher-order ocular aberrations for accurate intraocular scatter estimation.

Blind Image Deblurring for Multiply Image Frames Based on an Iterative Algorithm

A novel algorithm based on an iterative and nonnegative algorithm has been developed for performing blind deconvolution on multiply degraded image frames. The algorithm naturally preserves the nonnegative constraint on the iterative solutions of blind deconvolution and can produce a restored image of high resolution. Furthermore, benefited from the interframe information, the neighbouring frame can be seen as degenerated from the same object image and different point spread function (PSF), so utilizing the result of the last frame to the initial estimate of the current frame can reduce iterative times and enhance the efficiency of the algorithm, meanwhile, the algorithm is free from the instability of numerical computation. Results of applying the algorithm to simulated and real degraded images are reported.

18F-FDG PET/CT heterogeneity quantification through textural features in the era of harmonisation programs: a focus on lung cancer.

Quantification of tumour heterogeneity in PET images has recently gained interest, but has been shown to be dependent on image reconstruction. This study aimed to evaluate the impact of the EANM/EARL accreditation program on selected 18F-FDG heterogeneity metrics. To carry out our study, we prospectively analysed 71 tumours in 60 biopsy-proven lung cancer patient acquisitions reconstructed with unfiltered point spread function (PSF) positron emission tomography (PET) images (optimised for diagnostic purposes), PSF-reconstructed images with a 7-mm Gaussian filter (PSF7) chosen to meet European Association of Nuclear Medicine (EANM) 1.0 harmonising standards, and EANM Research Ltd. (EARL)-compliant ordered subset expectation maximisation (OSEM) images. Delineation was performed with fuzzy locally adaptive Bayesian (FLAB) algorithm on PSF images and reported on PSF7 and OSEM ones, and with a 50% standardised uptake values (SUV)max threshold (SUVmax50%) applied independently to each image. Robust and repeatable heterogeneity metrics including 1st-order [area under the curve of the cumulative histogram (CHAUC)], 2nd-order (entropy, correlation, and dissimilarity), and 3rd-order [high-intensity larger area emphasis (HILAE) and zone percentage (ZP)] textural features (TF) were statistically compared. Volumes obtained with SUVmax50% were significantly smaller than FLAB-derived ones, and were significantly smaller in PSF images compared to OSEM and PSF7 images. PSF-reconstructed images showed significantly higher SUVmax and SUVmean values, as well as heterogeneity for CHAUC, dissimilarity, correlation, and HILAE, and a wider range of heterogeneity values than OSEM images for most of the metrics considered, especially when analysing larger tumours. Histological subtypes had no impact on TF distribution. No significant difference was observed between any of the considered metrics (SUV or heterogeneity features) that we extracted from OSEM and PSF7 reconstructions. Furthermore, the distributions of TF for OSEM and PSF7 reconstructions according to tumour volumes were similar for all ranges of volumes. PSF reconstruction with Gaussian filtering chosen to meet harmonising standards resulted in similar SUV values and heterogeneity information as compared to OSEM images, which validates its use within the harmonisation strategy context. However, unfiltered PSF-reconstructed images also showed higher heterogeneity according to some metrics, as well as a wider range of heterogeneity values than OSEM images for most of the metrics considered, especially when analysing larger tumours. This suggests that, whenever available, unfiltered PSF images should also be exploited to obtain the most discriminative quantitative heterogeneity features.

19-3:Invited Paper: Computational 3D Imaging - PSF Engineering for Depth from Defocus -

A digital camera industry has been developed in a decade and has a lot of applications equipped with PC and mobile phone etc. However, optics and basic principle of image projection is not changed in latest digital camera. Computational imaging is a new research area for developing new imaging strategy for combining optics and processing of the digital imaging. Camera optics, such as lens and aperture, make an image on a sensor. The quality of the image is decided by the optical transfer function called point spread function (PSF). Computation imaging engineers the PSF for imaging and produces improved quality or function of the image after processing. I will introduce some examples of the PSF engineering methods; coded aperture, focus sweep in computation imaging, and show the coding improve the depth estimation by Depth from Defocus (DFD) application.

Effect of masking phase-only holograms on the quality of reconstructed images.

A phase-only hologram modulates the phase of the incident light and diffracts it efficiently with low energy loss because of the minimum absorption. Much research attention has been focused on how to generate phase-only holograms, and little work has been done to understand the effect and limitation of their partial implementation, possibly due to physical defects and constraints, in particular as in the practical situations where a phase-only hologram is confined or needs to be sliced or tiled. The present study simulates the effect of masking phase-only holograms on the quality of reconstructed images in three different scenarios with different filling factors, filling positions, and illumination intensity profiles. Quantitative analysis confirms that the width of the image point spread function becomes wider and the image quality decreases, as expected, when the filling factor decreases, and the image quality remains the same for different filling positions as well. The width of the image point spread function as derived from different filling factors shows a consistent behavior to that as measured directly from the reconstructed image, especially as the filling factor becomes small. Finally, mask profiles of different shapes and intensity distributions are shown to have more complicated effects on the image point spread function, which in turn affects the quality and textures of the reconstructed image.

The edge artifact in the point-spread function-based PET reconstruction at different sphere-to-background ratios of radioactivity.

The aim of this study was to quantitatively evaluate the edge artifacts in PET images reconstructed using the point-spread function (PSF) algorithm at different sphere-to-background ratios of radioactivity (SBRs). We used a NEMA IEC body phantom consisting of six spheres with 37, 28, 22, 17, 13 and 10 mm in inner diameter. The background was filled with (18)F solution with a radioactivity concentration of 2.65 kBq/mL. We prepared three sets of phantoms with SBRs of 16, 8, 4 and 2. The PET data were acquired for 20 min using a Biograph mCT scanner. The images were reconstructed with the baseline ordered subsets expectation maximization (OSEM) algorithm, and with the OSEM + PSF correction model (PSF). For the image reconstruction, the number of iterations ranged from one to 10. The phantom PET image analyses were performed by a visual assessment of the PET images and profiles, a contrast recovery coefficient (CRC), which is the ratio of SBR in the images to the true SBR, and the percent change in the maximum count between the OSEM and PSF images (Δ % counts). In the PSF images, the spheres with a diameter of 17 mm or larger were surrounded by a dense edge in comparison with the OSEM images. In the spheres with a diameter of 22 mm or smaller, an overshoot appeared in the center of the spheres as a sharp peak in the PSF images in low SBR. These edge artifacts were clearly observed in relation to the increase of the SBR. The overestimation of the CRC was observed in 13 mm spheres in the PSF images. In the spheres with a diameter of 17 mm or smaller, the Δ % counts increased with an increasing SBR. The Δ % counts increased to 91 % in the 10-mm sphere at the SBR of 16. The edge artifacts in the PET images reconstructed using the PSF algorithm increased with an increasing SBR. In the small spheres, the edge artifact was observed as a sharp peak at the center of spheres and could result in overestimation.

Blind single-image super resolution based on compressive sensing

Blind super resolution is an interesting area in image processing that can restore high resolution (HR) image without requiring prior information of the volatile point spread function (PSF). In this paper, a novel framework is proposed for blind single-image super resolution (SISR) problem based on compressive sensing (CS) framework that is one of the first works that considers general PSFs. The fundamental idea in the proposed approach is to use sparsity on a known sparse transform domain as a powerful regularizer in both the image and blur domains. Therefore, a new cost function with respect to the unknown HR image patch and PSF kernel is presented and minimization is performed based on two subproblems that are modeled similar to that of CS. Simulation results demonstrate the effectiveness of the proposed algorithm that is competitive with methods that use multiple LR images to achieve a single HR image.

Multimodal Partial-Volume Correction: Application to 18F-Fluoride PET/CT Bone Metastases Studies.

(18)F-fluoride PET/CT offers the opportunity for accurate skeletal metastasis staging, compared with conventional imaging methods. (18)F-fluoride is a bone-specific tracer whose uptake depends on osteoblastic activity. Because of the resulting increase in bone mineralization and sclerosis, the osteoblastic process can also be detected morphologically in CT images. Although CT is characterized by high resolution, the potential of PET is limited by its lower spatial resolution and the resulting partial-volume effect. In this context, the synergy between PET and CT presents an opportunity to resolve this limitation using a novel multimodal approach called synergistic functional-structural resolution recovery (SFS-RR). Its performance is benchmarked against current resolution recovery technology using the point-spread function (PSF) of the scanner in the reconstruction procedure. The SFS-RR technique takes advantage of the multiresolution property of the wavelet transform applied to both functional and structural images to create a high-resolution PET image that exploits the structural information of CT. Although the method was originally conceived for PET/MR imaging of brain data, an ad hoc version for whole-body PET/CT is proposed here. Three phantom experiments and 2 datasets of metastatic bone (18)F-fluoride PET/CT images from primary prostate and breast cancer were used to test the algorithm performances. The SFS-RR images were compared with the manufacturer's PSF-based reconstruction using the standardized uptake value (SUV) and the metabolic volume as metrics for quantification. When compared with standard PET images, the phantom experiments showed a bias reduction of 14% in activity and 1.3 cm(3) in volume estimates for PSF images and up to 20% and 2.5 cm(3) for the SFS-RR images. The SFS-RR images were characterized by a higher recovery coefficient (up to 60%) whereas noise levels remained comparable to those of standard PET. The clinical data showed an increase in the SUV estimates for SFS-RR images up to 34% for peak SUV and 50% for maximum SUV and mean SUV. Images were also characterized by sharper lesion contours and better lesion detectability. The proposed methodology generates PET images with improved quantitative and qualitative properties. Compared with standard methods, SFS-RR provides superior lesion segmentation and quantification, which may result in more accurate tumor characterization.

Sub-millimeter T2 weighted fMRI at 7 T: comparison of 3D-GRASE and 2D SE-EPI.

Functional magnetic resonance imaging (fMRI) allows studying human brain function non-invasively up to the spatial resolution of cortical columns and layers. Most fMRI acquisitions rely on the blood oxygenation level dependent (BOLD) contrast employing T*2 weighted 2D multi-slice echo-planar imaging (EPI). At ultra-high magnetic field (i.e., 7 T and above), it has been shown experimentally and by simulation, that T2 weighted acquisitions yield a signal that is spatially more specific to the site of neuronal activity at the cost of functional sensitivity. This study compared two T2 weighted imaging sequences, inner-volume 3D Gradient-and-Spin-Echo (3D-GRASE) and 2D Spin-Echo EPI (SE-EPI), with evaluation of their imaging point-spread function (PSF), functional specificity, and functional sensitivity at sub-millimeter resolution. Simulations and measurements of the imaging PSF revealed that the strongest anisotropic blurring in 3D-GRASE (along the second phase-encoding direction) was about 60% higher than the strongest anisotropic blurring in 2D SE-EPI (along the phase-encoding direction). In a visual paradigm, the BOLD sensitivity of 3D-GRASE was found to be superior due to its higher temporal signal-to-noise ratio (tSNR). High resolution cortical depth profiles suggested that the contrast mechanisms are similar between the two sequences, however, 2D SE-EPI had a higher surface bias owing to the higher T*2 contribution of the longer in-plane EPI echo-train for full field of view compared to the reduced field of view of zoomed 3D-GRASE.

Polarization Aberrations in Astronomical Telescopes: The Point Spread Function

Detailed knowledge of the image of the point spread function (PSF) is necessary to optimize astronomical coronagraph masks and to understand potential sources of errors in astrometric measurements. The PSF for astronomical telescopes and instruments depends not only on geometric aberrations and scalar wave diffraction but also on those wavefront errors introduced by the physical optics and the polarization properties of reflecting and transmitting surfaces within the optical system. These vector wave aberrations, called polarization aberrations, result from two sources: (1) the mirror coatings necessary to make the highly reflecting mirror surfaces, and (2) the optical prescription with its inevitable non-normal incidence of rays on reflecting surfaces. The purpose of this article is to characterize the importance of polarization aberrations, to describe the analytical tools to calculate the PSF image, and to provide the background to understand how astronomical image data may be affected. To show the order of magnitude of the effects of polarization aberrations on astronomical images, a generic astronomical telescope configuration is analyzed here by modeling a fast Cassegrain telescope followed by a single 90° deviation fold mirror. All mirrors in this example use bare aluminum reflective coatings and the illumination wavelength is 800 nm. Our findings for this example telescope are: (1) The image plane irradiance distribution is the linear superposition of four PSF images: one for each of the two orthogonal polarizations and one for each of two cross-coupled polarization terms. (2) The PSF image is brighter by 9% for one polarization component compared to its orthogonal state. (3) The PSF images for two orthogonal linearly polarization components are shifted with respect to each other, causing the PSF image for unpolarized point sources to become slightly elongated (elliptical) with a centroid separation of about 0.6 mas. This is important for both astrometry and coronagraph applications. (4) Part of the aberration is a polarization-dependent astigmatism, with a magnitude of 22 milliwaves, which enlarges the PSF image. (5) The orthogonally polarized components of unpolarized sources contain different wavefront aberrations, which differ by approximately 32 milliwaves. This implies that a wavefront correction system cannot optimally correct the aberrations for all polarizations simultaneously. (6) The polarization aberrations couple small parts of each polarization component of the light (∼10-4) into the orthogonal polarization where these components cause highly distorted secondary, or “ghost” PSF images. (7) The radius of the spatial extent of the 90% encircled energy of these two ghost PSF image is twice as large as the radius of the Airy diffraction pattern. Coronagraphs for terrestrial exoplanet science are expected to image objects 10-10, or 6 orders of magnitude less than the intensity of the instrument-induced “ghost” PSF image, which will interfere with exoplanet measurements. A polarization aberration expansion which approximates the Jones pupil of the example telescope in six polarization terms is presented in the appendix. Individual terms can be associated with particular polarization defects. The dependence of these terms on angles of incidence, numerical aperture, and the Taylor series representation of the Fresnel equations lead to algebraic relations between these parameters and the scaling of the polarization aberrations. These “design rules” applicable to the example telescope are collected in § . Currently, exoplanet coronagraph masks are designed and optimized for scalar diffraction in optical systems. Radiation from the “ghost” PSF image leaks around currently designed image plane masks. Here, we show a vector-wave or polarization optimization is recommended. These effects follow from a natural description of the optical system in terms of the Jones matrices associated with each ray path of interest. The importance of these effects varies by orders of magnitude between different optical systems, depending on the optical design and coatings selected. Some of these effects can be calibrated while others are more problematic. Polarization aberration mitigation methods and technologies to minimize these effects are discussed. These effects have important implications for high-contrast imaging, coronagraphy, and astrometry with their stringent PSF image symmetry and scattered light requirements.

Point spread functions for earthquake source imaging: an interpretation based on seismic interferometry

SUMMARY Recently, various methods have been proposed and applied for earthquake source imaging, and theoretical relationships among the methods have been studied. In this study, we make a follow-up theoretical study to better understand the meanings of earthquake source imaging. For imaging problems, the point spread function (PSF) is used to describe the degree of blurring and degradation in an obtained image of a target object as a response of an imaging system. In this study, we formulate PSFs for earthquake source imaging. By calculating the PSFs, we find that waveform source inversion methods remove the effect of the PSF and are free from artefacts. However, the other source imaging methods are affected by the PSF and suffer from the effect of blurring and degradation due to the restricted distribution of receivers. Consequently, careful treatment of the effect is necessary when using the source imaging methods other than waveform inversions. Moreover, the PSF for source imaging is found to have a link with seismic interferometry with the help of the source–receiver reciprocity of Green’s functions. In particular, the PSF can be related to Green’s function for cases in which receivers are distributed so as to completely surround the sources. Furthermore, the PSF acts as a low-pass filter. Given these considerations, the PSF is quite useful for understanding the physical meaning of earthquake source imaging.

Color difference threshold of chromostereopsis induced by flat display emission.

The study of chromostereopsis has gained attention in the backdrop of the use of computer displays in daily life. In this context, we analyze the illusory depth sense using planar color images presented on a computer screen. We determine the color difference threshold required to induce an illusory sense of depth psychometrically using a constant stimuli paradigm. Isoluminant stimuli are presented on a computer screen, which stimuli are aligned along the blue–red line in the computer display CIE xyY color space. Stereo disparity is generated by increasing the color difference between the central and surrounding areas of the stimuli with both areas consisting of random dots on a black background. The observed altering of illusory depth sense, thus also stereo disparity is validated using the “center-of-gravity” model. The induced illusory sense of the depth effect undergoes color reversal upon varying the binocular lateral eye pupil covering conditions (lateral or medial). Analysis of the retinal image point spread function for the display red and blue pixel radiation validates the altering of chromostereopsis retinal disparity achieved by increasing the color difference, and also the chromostereopsis color reversal caused by varying the eye pupil covering conditions.

New deconvolution method for microscopic images based on the continuous Gaussian radial basis function interpolation model.

A deconvolution method based on the Gaussian radial basis function (GRBF) interpolation is proposed. Both the original image and Gaussian point spread function are expressed as the same continuous GRBF model, thus image degradation is simplified as convolution of two continuous Gaussian functions, and image deconvolution is converted to calculate the weighted coefficients of two-dimensional control points. Compared with Wiener filter and Lucy-Richardson algorithm, the GRBF method has an obvious advantage in the quality of restored images. In order to overcome such a defect of long-time computing, the method of graphic processing unit multithreading or increasing space interval of control points is adopted, respectively, to speed up the implementation of GRBF method. The experiments show that based on the continuous GRBF model, the image deconvolution can be efficiently implemented by the method, which also has a considerable reference value for the study of three-dimensional microscopic image deconvolution.

Chiral Nanostructures Studied Using Polarization-Dependent NOLES Imaging

The Nonlinear Optical Localization using Electromagnetic Surface fields (NOLES) imaging technique was used to generate optical images in which the position of a chiral object could be determined with nanometer precision. Asymmetric gold bowtie nanostructures were used as a model system with 2D chirality. The bowties functioned as a chiral nonlinear medium that converted the fundamental of a Ti:sapphire laser to its second harmonic frequency. The bowties consisted of two lithographically prepared equilateral triangles (base = 75 nm, height = 85 nm, thickness = 25 nm) separated by a 20 nm gap. Asymmetric bowties were formed by lateral displacement of one triangle by 10 nm, yielding C2 point group symmetry. The chirality of the bowtie nanostructures was confirmed via nonzero second-harmonic generation circular dichroism (SHG-CDR) ratios, which came from single-particle SHG measurements. The SHG-CDR ratios were validated using numerical finite difference time domain simulations that quantified the relative magnitudes of gap-localized electromagnetic fields at the harmonic frequency resulting from excitation by left and right circularly (LCP and RCP) and linearly polarized fundamental waves. The relative electric dipolar and magnetic dipolar contributions to the SHG responses were determined using single-particle continuous polarization variation (CPV) SHG measurements. The spatial localization precision obtainable for individual chiral nanostructures was determined by statistical analysis of the SHG image point spread function. Our results demonstrated that both the chiral image contrast, which resulted from LCP and RCP excitation, and the corresponding localization precision was dependent upon the relative magnetic dipole/electric dipole ratio (G/F). A localization precision of 1.13 ± 0.13 nm and left-to-right image enhancements of 400% were obtained for bowties with the highest G/F ratios using 5 s frame exposure times. The polarization dependence and magnetic dipole amplification confirmed here demonstrate that the NOLES imaging technique is a powerful method for studying chiral specimens with high spatial precision.

Magnetoacoustic tomography with magnetic induction for high‐resolution bioimepedance imaging through vector source reconstruction under the static field of MRI magnet

Magnetoacoustic tomography with magnetic induction (MAT-MI) is an imaging modality to reconstruct the electrical conductivity of biological tissue based on the acoustic measurements of Lorentz force induced tissue vibration. This study presents the feasibility of the authors' new MAT-MI system and vector source imaging algorithm to perform a complete reconstruction of the conductivity distribution of real biological tissues with ultrasound spatial resolution. In the present study, using ultrasound beamformation, imaging point spread functions are designed to reconstruct the induced vector source in the object which is used to estimate the object conductivity distribution. Both numerical studies and phantom experiments are performed to demonstrate the merits of the proposed method. Also, through the numerical simulations, the full width half maximum of the imaging point spread function is calculated to estimate of the spatial resolution. The tissue phantom experiments are performed with a MAT-MI imaging system in the static field of a 9.4 T magnetic resonance imaging magnet. The image reconstruction through vector beamformation in the numerical and experimental studies gives a reliable estimate of the conductivity distribution in the object with a ∼ 1.5 mm spatial resolution corresponding to the imaging system frequency of 500 kHz ultrasound. In addition, the experiment results suggest that MAT-MI under high static magnetic field environment is able to reconstruct images of tissue-mimicking gel phantoms and real tissue samples with reliable conductivity contrast. The results demonstrate that MAT-MI is able to image the electrical conductivity properties of biological tissues with better than 2 mm spatial resolution at 500 kHz, and the imaging with MAT-MI under a high static magnetic field environment is able to provide improved imaging contrast for biological tissue conductivity reconstruction.

运动模糊图像点扩散函数的频谱估计法

运动模糊图像点扩散函数的频谱估计法

3D-image restoration technique using Genetic Algorithm to solve blurring problems of images

Most images may not be sharp and clear due to various reasons like noise interference and is said to be in a blurred condition. Image de-blurring is fundamental in making pictures sharp and useful. Normally, along with the input blurred image, Point Spread Function (PSF) of the original image is required for the process of restoration and de-blurring. In this paper, we introduce a technique for image restoration by Richardson–Lucy algorithm where the optimised PSF is generated by the use of Genetic Algorithm (GA). Use of optimised PSF ensures that our proposed technique does not need the original image for the de-blurring purpose and can be greatly beneficial in the real time scenario cases. The dataset used for the evaluation of the proposed technique are real 3D images and the evaluation metrics used are peak signal-to-noise ratio (PSNR), Second-Derivative like Measure of Enhancement (SDME) and mean squared error (MSE). The technique is compared with existing techniques such as de-convolution method, regularisation filter, Wiener filter and Richardson–Lucy algorithm. From the results, we can observe that our proposed technique has achieved higher PSNR and SDME values and lower MSE values when compared with other techniques. We have achieved average PSNR of 70·94, SDME of 71·46 and MSE of 0·0063. The values obtained show the superior performance of the proposed technique.