Minimum Artifacts Research Articles

Spatial resolution in optical coherence elastography of bounded media.

Dynamic optical coherence elastography (OCE) tracks mechanical wave propagation in the subsurface region of tissue to image its shear modulus. For bulk shear waves, the lateral resolution of the reconstructed modulus map (i.e., elastographic resolution) can approach that of optical coherence tomography (OCT), typically a few tens of microns. Here we perform comprehensive numerical simulations and acoustic micro-tapping OCE experiments to show that for the typical situation of guided wave propagation in bounded media, such as cornea, the elastographic resolution cannot reach the OCT resolution and is mainly defined by the thickness of the bounded tissue layer. We considered the excitation of both broadband and quasi-harmonic guided waves in a bounded, isotropic medium. Leveraging the properties of broadband pulses, a robust method for modulus reconstruction with minimum artifacts at interfaces is demonstrated. In contrast, tissue bounding creates large instabilities in the phase of harmonic waves, leading to serious artifacts in modulus reconstructions.

Deep Learning-Based Multimodal 3 T MRI for the Diagnosis of Knee Osteoarthritis.

The objective of this study was to investigate the application effect of deep learning model combined with different magnetic resonance imaging (MRI) sequences in the evaluation of cartilage injury of knee osteoarthritis (KOA). Specifically, an image superresolution algorithm based on an improved multiscale wide residual network model was proposed and compared with the single-shot multibox detector (SSD) algorithm, superresolution convolutional neural network (SRCNN) algorithm, and enhanced deep superresolution (EDSR) algorithm. Meanwhile, 104 patients with KOA diagnosed with cartilage injury were selected as the research subjects and underwent MRI scans, and the diagnostic performance of different MRI sequences was analyzed using arthroscopic results as the gold standard. It was found that the image reconstructed by the model in this study was clear enough, with minimum noise and artifacts, and the overall quality was better than that processed by other algorithms. Arthroscopic analysis found that grade I and grade II lesions concentrated on patella (26) and femoral trochlear (15). In addition to involving the patella and femoral trochlea, grade III and grade IV lesions gradually developed into the medial and lateral articular cartilage. The 3D-DS-WE sequence was found to be the best sequence for diagnosing KOA injury, with high diagnostic accuracy of over 95% in grade IV lesions. The consistency test showed that the 3D-DESS-WE sequence and T2∗ mapping sequence had a strong consistency with the results of arthroscopy, and the Kappa consistency test values were 0.748 and 0.682, respectively. In conclusion, MRI based on deep learning could clearly show the cartilage lesions of KOA. Of different MRI sequences, 3D-DS-WE sequence and T2∗ mapping sequence showed the best diagnosis results for different degrees of KOA injury.

New Exponential Scoring Functions for Diet Quality Indexes Solve Problems Caused by Truncation

Diet quality indexes, including the Healthy Eating Index, assess diets based on usual dietary intakes and a scoring function. Nearly all diet quality indexes use scoring functions that have floors and ceilings, thereby truncating the scores and losing information about intakes outside the scoring range. This score truncation has 2 important impacts: 1) the index does not reflect all intakes; and 2) the assumption that measurement error in intake reporting has a neutral impact on the diet quality score cannot be upheld. Our main objective was to devise new diet quality scoring functions that eliminate truncation and its attendant problems. Seven desirable properties of a new scoring function were identified: 1) avoid truncations in component scoring to prevent information loss and to provide scoring sensitivity in the currently truncated regions; 2) reduce dependency on the accuracy of dietary standards; 3) minimize measurement error bias and subsequent misclassification; 4) relate plausibly to biological processes; 5) possess desirable mathematical and statistical properties; 6) have simple representations that are easy to calculate and add minimum artifacts of their own; and 7) otherwise closely mimic existing scoring functions. The recommended replacement for piecewise-linear scoring is a family of scoring functions based on exponentials. For components where higher intakes are better, the function is a single exponential. For components where lower intakes are better, the function is a concave-convex mirrored pair of exponentials. The proposed exponential scoring functions have all 7 desired properties. The proposed exponential scoring functions will improve the usefulness of dietary scoring indexes by eliminating truncations. Compared to existing scoring functions, the use of exponentials makes the scores more inclusive of very high and very low intakes, reduces measurement error bias, and is less sensitive to the exact placement of the scoring standards.

A general phase ambiguity suppression algorithm combining geometric constraints and temporal phase unwrapping

In fringe projection profilometry, various sophisticated temporal phase unwrapping (TPU) methods are conceived to recover a continuous absolute phase map. However, phase ambiguity is a thorny problem that affects measurement accuracy, which is deeply troubled by researchers. Dealing with the challenge, a universal algorithm (G-TPU) uniting geometric constraints phase unwrapping (GCPU) and TPU is proposed to comb out the phase ambiguity. Firstly, The invalid phase map or continuous relative phase map is unwrapped by GCPU with the minimum artifact. Then the unwrapped phas map is divided into several object regions, and the effective phase range (EPR) and invalid phase range (IPR) of each object region are determined by the proposed edge determination and image filling algorithm. Finally, through the statistical analysis of the decoded codewords, the relative orders are added to each EPR and IPR, and the absolute phase map is obtained. The proposed method inherits the complementary advantages of absolute position determination and strong robustness in TPU and GCPU respectively. Since GCPU does not need additional fringe patterns, it can be perfectly integrated into all TPU methods. The experimental results demonstrate the success of the proposed method combining GCPU and TPU.

Multispectral Interlaced Sparse Sampling Photoacoustic Tomography.

Multispectral photoacoustic tomography (PAT) is capable of resolving tissue chromophore distribution based on spectral un-mixing. It works by identifying the absorption spectrum variations from a sequence of photoacoustic images acquired at multiple illumination wavelengths. Due to multispectral acquisition, this inevitably creates a large dataset. To cut down the data volume, sparse sampling methods that reduce the number of detectors have been developed. However, image reconstruction of sparse sampling PAT is challenging because of insufficient angular coverage. During spectral un-mixing, these inaccurate reconstructions will further amplify imaging artefacts and contaminate the results. To solve this problem, we present the interlaced sparse sampling (ISS) PAT, a method that involved: 1) a novel scanning-based image acquisition scheme in which the sparse detector array rotates while switching illumination wavelength, such that a dense angular coverage could be achieved by using only a few detectors; and 2) a corresponding image reconstruction algorithm that makes use of an anatomical prior image created from the ISS strategy to guide PAT image computation. Reconstructed from the signals acquired at different wavelengths (angles), this self-generated prior image fuses multispectral and angular information, and thus has rich anatomical features and minimum artefacts. A specialized iterative imaging model that effectively incorporates this anatomical prior image into the reconstruction process is also developed. Simulation, phantom, and in vivo animal experiments showed that even under 1/6 or 1/8 sparse sampling rate, our method achieved comparable image reconstruction and spectral un-mixing results to those obtained by conventional dense sampling method.

Quality assessment tool for performance measurement of image contrast enhancement methods

An objective image quality assessment tool is proposed to measure image enhancement quality with emphasis on contrast. In the proposed tool, which is based on maximizing contrast with minimum artefact (MCMA), local and global properties of an image are measured through pixel-wise and histogram-wise features, respectively. To this aim, three sub-measures are introduced, each of which able to detect one contrast-related quality aspect: (i) low dynamic range of image; (ii) histogram shape preservation during image enhancement process; and (iii) local pixel diversity. These sub-measures are combined through a subjective test to adapt them to the mean opinion scores (MOSs) of a diverse set of training contrast-enhanced images. A regression algorithm performs the adaptation by fitting the three sub-measures to the MOS values and finding an optimal linear combination by maximizing the Pearson correlation. In order to evaluate the performance of the MCMA algorithm, another independent, subsequent, subjective test was performed on a set of images enhanced by various known contrast enhancement algorithms to obtain MOS values and to compare them with the output of the proposed MCMA method. The experimental results show that MCMA has the highest correlation to the MOS when compared to the existing tested contrast measurement tools.

Image Denoising: Issues and Challenges

Extracting noise coefficients from images to make them more informative is of critical importance in plenty of applications. There have been a lot of denoising techniques existing in the literature. However, the fidelity of the denoising algorithm is determined by the quality of the reconstructed image. Minimum artifacts and better preservation of geometrical details such as edges and texture reflect efficient image reconstruction. This paper presents a review of some remarkable trends in the field of denoising. The foremost objective of this study is to provide an understanding of research in the context of detail preserving denoising. In this paper, we also explore how denoising challenges force growth of denoising techniques from spatial domain filters to transform domain, from transform domain to hybrid domain and then to dictionary learning based methods. While all these approaches aim at productive denoising, they possess different assumptions, advantages, and shortcomings. This paper also provides us a deep understanding of which method to be adopted to obtain the most reliable results.

Singing voice separation using mono-channel mask

Separating singing voice from monaural song recording is a highly difficult task. Still it is important because it has many applications such as singer identification, lyrics recognition, and melody extraction. Difficulty arises due to many musical instruments involved and time-varying spectral overlap between singing voice and music. The goal of singing voice separation is to extract singing voice from the given monaural song recording with minimum artefacts and musical interference. We propose a three stage system for singing voice separation which helps to improve intelligibility and perceptual quality of the separated output. In the first stage, modified sub-harmonic summation algorithm finds pitch of the singing voice and its harmonic components. Here, we create a binary mask. In the second stage, frames i.e. the masked spectral amplitudes are classified as singing and non-singing frames by using a combination of Gammatone frequency cepstral coefficients (GFCC) and Mel-frequency cepstral coefficients (MFCC) features. Lastly, mono-channel mask is created and signal amplitude correction is done using kurtosis measure. We synthesize the estimate of singing voice using both binary mask and mono-channel mask. It is observed that the singing voice separated using mono-channel mask improves the GNSDR score. Performance of the proposed system is compared with the other methods, where it presents excellent improvement in terms of GNSDR. It produces higher GNSDR scores in case of two different datasets.

Near Range Radar Image Reconstruction Algorithm by Weighted Envelopes Transformation

We proposed a methodology to apply inverse boundary scattering transform to process complex radar data with minimum imaging artifacts. Unlike other boundary extraction-based methods, such as shape estimation algorithm based on boundary scattering transform and extraction of directly scattered waves, the developed approach does not rely on peaks of signals, does not require to connect points to quasi wavefronts, and it is numerically stable and robust. Instead of quasi wavefronts extraction, the method process huge amount of the wave-tracking lines, match the weight values to them, and apply multistage filtration based on the first and second derivatives. It makes the developed method to be able to be used for processing cluttered data like GPR. Using the experimentally obtained GPR profile, we demonstrated that the method allows separating the buried objects from clutter, noise, and imaging artifacts. Compared to conventional diffraction stacking method, weighted envelopes transformation results show good clearness of the targets, which makes the profiles easy to interpret. A number of filtration parameters over huge number of extracted features provide good flexibility and wide applicability of our approach.

Effects of non-physiological blood pressure artefacts on cerebral autoregulation

Cerebral autoregulation refers to the brain’s regulation mechanisms that aim to maintain the cerebral blood flow approximately constant. It is often assessed by the autoregulation index (ARI). ARI uses arterial blood pressure and cerebral blood flow velocity time series to produce a ten-scale index of autoregulation performance (0 denoting the absence of and 9 the strongest autoregulation). Unfortunately, data are rarely free from various artefacts. Here, we consider four of the most common non-physiological blood pressure artefacts (saturation, square wave, reduced pulse pressure and impulse) and study their effects on ARI for a range of different artefact sizes. We show that a sufficiently large saturation and square wave always result in ARI reaching the maximum value of 9. The pulse pressure reduction and impulse artefact lead to more diverse behaviour. Finally, we characterized the critical size of artefacts, defined as the minimum artefact size that, on average, leads to a 10% deviation of ARI.

Analisis Informasi Citra MRI Vertebra Servikal Potongan Axial dengan Penggunaan Flow Compensation antara Pembobotan T2 Sekuens Turbo Spin Echo (TSE) dan gradient echo (GRE)

Background: Magnetic Resonance Imaging (MRI) examination of the cervical spine axial slices with T2 weighted flow is often contained artifacts that interfere image result, so it uses flow compensation technique. Axial slices of T2 weighted may use TSE or GRE sequences. This research aims to determine differences in MRI image information of cervical spine axial slices using flow compensation between T2 weighted turbo spin echo (TSE) and gradient echo (GRE) sequences and to get better image information between that both sequences.Methods: This research was a quantitative study with an experimental approach. Data were collected from May to June 2016 in Radiology Installation of Haji Surabaya Hospital using a questionnaire to three respondents. Data were analyzed by statistical tests with SPSS 16 software using Wilcoxon test to determine differences level in image information between T2 weighted TSE and GRE sequences, mean rank value from Wilcoxon test and crosstabulation test to get better image information.Results: There were differences in MRI image information of cervical spine axial slices with using flow compensation between T2 weighted TSE and GRE sequences with p-value was 0.005 (p 0.05). This difference was due to the differences of parameter characteristics between both sequences and T2* GRE was more sensitive to flow to the organ than the TSE. Better MRI image information of cervical spine axial slices using flow compensation was T2* GRE sequence shown by the mean rank 5.50.T2*. GRE was better than T2 TSE because it could show the anatomy of the cervical clearly and informatively, the anatomy of the spinal cord, CSF, neural foramen, intraforaminal structure, corpus vertebrae, disc and the minimum artifacts. While on the anatomy of the facet joint was no significant difference between the TSE and GRE sequences.Conclusion: There were differences in the MRI image information of cervical spine axial slices using flow compensation between T2 weighted TSE and GRE sequences. Better image information was T2* GRE sequence.

Bare-earth extraction and DTM generation from photogrammetric point clouds including the use of an existing lower-resolution DTM

ABSTRACTA method of extracting bare-earth points from photogrammetric point clouds by partially using an existing lower resolution digital terrain model (DTM) is presented. The bare-earth points are extracted based on a threshold defined by local slope. The local slope is estimated from the lower resolution DTM. A gridded DTM is then interpolated from the extracted bare-earth points. Five different interpolation algorithms are implemented and evaluated to identify the most suitable interpolation method for such non-uniformly scattered data. The algorithm is tested on four test sites with varying topographic and ground cover characteristics. The results are evaluated against a reference DTM created using aerial laser scanning. The deviations of the extracted bare-earth points, and the interpolated DTM, from the reference DTM increases with increasing forest canopy density and terrain roughness. The DTM created by the method is significantly closer to the reference DTM than the lower resolution national DTM. The ANUDEM (Australian National University Digital Elevation Modelling) interpolation method is found to be the best performing interpolation method in terms of reducing the deviations and in terms of modelling the terrain realistically with minimum artefacts, although the differences among the interpolation methods are not considerably large.

BARE-EARTH EXTRACTION AND DTM GENERATION FROM PHOTOGRAMMETRIC POINT CLOUDS WITH A PARTIAL USE OF AN EXISTING LOWER RESOLUTION DTM

Abstract. A method of extracting bare-earth points from photogrammetric point clouds by partially using an existing lower resolution digital terrain model (DTM) is presented. The bare-earth points are extracted based on a threshold defined by local slope. The local slope is estimated from the lower resolution DTM. A gridded DTM is then interpolated from the extracted bare-earth points. Five different interpolation algorithms are implemented and evaluated to identify the most suitable interpolation method for such non-uniformly scattered data. The algorithm is tested on four test sites with varying topographic and ground cover characteristics. The results are evaluated against a reference DTM created using aerial laser scanning. The deviations of the extracted bare-earth points, and the interpolated DTM, from the reference DTM increases with increasing forest canopy density and terrain roughness. The DTM created by the method is significantly closer to the reference DTM than the lower resolution national DTM. The ANUDEM (Australian National University Digital Elevation Modelling) interpolation method is found to be the best performing interpolation method in terms of reducing the deviations and in terms of modelling the terrain realistically with minimum artefacts, although the differences among the interpolation methods are not considerably large.

BARE-EARTH EXTRACTION AND DTM GENERATION FROM PHOTOGRAMMETRIC POINT CLOUDS WITH A PARTIAL USE OF AN EXISTING LOWER RESOLUTION DTM

A method of extracting bare-earth points from photogrammetric point clouds by partially using an existing lower resolution digital terrain model (DTM) is presented. The bare-earth points are extracted based on a threshold defined by local slope. The local slope is estimated from the lower resolution DTM. A gridded DTM is then interpolated from the extracted bare-earth points. Five different interpolation algorithms are implemented and evaluated to identify the most suitable interpolation method for such non-uniformly scattered data. The algorithm is tested on four test sites with varying topographic and ground cover characteristics. The results are evaluated against a reference DTM created using aerial laser scanning. The deviations of the extracted bare-earth points, and the interpolated DTM, from the reference DTM increases with increasing forest canopy density and terrain roughness. The DTM created by the method is significantly closer to the reference DTM than the lower resolution national DTM. The ANUDEM (Australian National University Digital Elevation Modelling) interpolation method is found to be the best performing interpolation method in terms of reducing the deviations and in terms of modelling the terrain realistically with minimum artefacts, although the differences among the interpolation methods are not considerably large.

Ultrastructural features of dentinoenamel junction revealed by focused gallium ion beam milling.

To take full advantage of focused ion beam (FIB) in preparation of ultrathin sections of biological tissues, we have used a cryo-milling process. In this study, extracted human teeth were scanned by optical coherence tomography to inspect the samples for intactness and to determine the area of interest. Then, the selected area of interest was cross-sectioned for examination under a confocal laser scanning microscope to determine the target location of the dentinoenamel junction (DEJ) that was later milled by cryo-FIB at preset parameters, followed by transmission electron microscope examination of the final sliced specimens for ultrastructural characterization. The proposed technique was able to outline the DEJ and to identify the different tooth layers in a single section, without artefacts or tissue damage. The DEJ was outlined as fine longitudinal projections intermingling between the solid electron-dense enamel and intricate electron-lucent hollow dentin. In conclusion, this study has shown the great potential of cryo-FIB in handling different biological tissues having different physical properties, with great precision and accuracy and minimum artefacts.

Optimum multiscale decomposition in NSCT-based single image super resolution

Goal of image super resolution (SR) is to enhance the size of an image without upsetting the information it carries. The information around the edges may get disturbed due to image SR process. The proposed novel approach conserved the information around edges using Non-sub sample contourlet transform (NSCT)-based learning technique. The NSCT constitutes multiscale decomposition as well as multidirectional decomposition of an image. The main contribution of the paper is to optimally select multiscale decomposition level that offers minimum learning error. The smoothness of soft edges is to be potted by soft edge smoothness prior. The learning process leads to appearance of unwanted outliers which are sustained by using a robust error norm. The cost function consisting of a global constraint term and soft edge smoothness prior is optimised using Iterative Back Projection approach. The proposed method is capable to reconstruct a high-resolution image with minimum edge artefacts.

CHARAKTERYSTYKA INTERFERENCJI POCHODZĄCYCH Z ARTEFAKTÓW MIĘŚNIOWYCH W SYGNAŁACH SŁUCHOWYCH POTENCJAŁÓW WYWOŁANYCH

BackgroundIt is well known that muscle artifacts negatively affect auditory evoked potential (AEP) recordings. However, the precise relation between the set of muscles involved and the specific AEP affected is not clear. Most audiologists believe that increase in the tension of any muscle in the body would affect all AEPs to the same extent, while some believe that only head and neck muscles affect AEPs. Logically, this relation will depend on the frequency characteristics of the muscle artifact. However, to the best of our knowledge, there is no scientific documentation of the extent of interference created by various muscle responses on auditory brainstem responses (ABRs), middle latency responses (MLRs), and late latency responses (LLRs). The present study therefore sought to analyse the minimum artifact rejection threshold required for ABR, MLR, and LLR under various artifact-inducing conditions.Material and MethodsThe present study involved 40 individuals of age 17 to 24 years. For each participant, the effects of muscle artifacts on three popular, clinically relevant AEPs (ABR, MLR, and LLR) were determined. First, recording was done in a rest condition where participants were seated in a reclining chair and asked to close their eyes and maintain a relaxed position. Then the participants were asked to carry out one of the following tasks: blink their eyes continuously; spread their lips; or stiffen their neck, hand, or leg muscles maximally. While tensing each of these set of muscles, the minimum artifact rejection threshold (MART) was noted.ResultsThe results showed that each of the artifact-inducing conditions affected the three target AEPs differently. At rest, there was no significant difference in MART across the three AEPs, but artifact-inducing conditions produced different effects.ConclusionsNot all artifacts affect every AEP equally. For good AEP recordings one needs to have a clear understanding of various muscle potentials and their relative effect on each AEP.

Adaptive directional decomposition in non sub sample contourlet transform domain for single image super resolution

The crucial point of research about single-image super-resolution is to enhance the size of an image without fiddle its quality. To conserve the quality of an enhanced image, a novel learning based approach in Non Sub Sampled Contourlet Transform (NSCT) domain is proposed in this paper. The NSCT constitute multiscale -multidirectional decomposition of an image. An algorithm, proposed for adaptive multidirectional decomposition picks up the optimal benefit of the directionality offered by NSCT. A sharp initialization, obtained via learning in NSCT domain, is able to generate a high resolution image with minimum edge artifacts. Experiments on various images show the effectiveness of the proposed algorithm.

Ex vivo visualization of the mouse otoconial layer compared with micro-computed tomography.

Micro-computed tomography (micro-CT) is useful for assessing the 3-dimensional (3D) morphology and age-related changes of the otoconial layer. Wriggle mouse Sagami (WMS) is a mutant of the plasma membrane Ca2+ ATPase type2 gene (Atp2b2) with deficits in the saccular otoconia. We examined the effectiveness of micro-CT in evaluating the otoconial layer of WMS and C57BL/6J mice. Otic capsules of C57BL/6J mice at different fixation time were examined using micro-CT to evaluate the effects of the fixation time on the otoconial layer. Otic capsules of Atp2b2(wri/wri), Atp2b2(wri/+), and Atp2b2(+/+) mice at P14, P21, and the age of 3 months were used to analyze age-related changes in the otoconial layer. A series of cross-section and 3D reconstructed images of the otoconial layer were obtained. The micro-CT findings were compared with the otic capsule findings cleared in methyl salicylate using stereomicroscopy. Micro-CT produced high-resolution images of the otoconial layer, thereby providing information regarding the spatial configuration and 3D curvature. There were no changes between the different fixation times. In the Atp2b2(wri/+) and Atp2b2(+/+) mice, the saccular and utricular otoconial layers were normal among all age groups. In the Atp2b2(wri/wri) mice, the saccular otoconial layer decreased on P14 and was absent on P21, whereas the utricular otoconial layer disappeared at 3 months of age. We obtained precise information regarding the mouse otoconial layer with minimum artifacts. This method is expected to improve our understanding of the physiologic function and age-related changes in otolith organs.

Phased array coil for implementing parallel MRI in intravascular imaging: A feasibility study

ABSTRACTThe use of intravascular MRI imaging of vessels will provide high quality images for improved diagnosis and treatment. An intravascular MR receive coil provides high SNR because of proximity to the tissue but respiratory and cardiovascular motion may affect the quality of acquired images. Parallel MRI provides a framework to reduce the scan time using multiple coils. This article presents a novel design of a Phased Array MR receive coil for intravascular imaging which can implement Parallel MRI. Cartesian and Radial GRAPPA are used as the main reconstruction algorithms. We demonstrate that Moving Segment Radial GRAPPA provides good image reconstruction with minimum artifacts when data is under‐sampled by a factor of 16. © 2015 Wiley Periodicals, Inc. Concepts Magn Reson Part A 43A: 267–276, 2015.