Correction Of Motion Artifacts Research Articles

Further Improving Image Quality of Cardiovascular Computed Tomography Angiography for Children With High Heart Rates Using Second-Generation Motion Correction Algorithm.

The state-of-art motion correction algorithm is inadequate for correcting motion artifacts in coronary arteries in cardiovascular computed tomography angiography (CCTA) for children with high heart rates, and even less effective for heart structures beyond coronary arteries. This study aimed to evaluate the effectiveness of a second-generation, whole-heart motion correction algorithm in improving the heart image quality of CCTA for children with high heart rates. Forty-two consecutive symptomatic cardiac patients with high heart rates (122.6 ± 18.8 beats/min) were enrolled. All patients underwent CCTA on a 256-row CT using a prospective electrocardiogram-triggered single-beat protocol. Images were reconstructed using a standard algorithm (STD), state-of-the-art first-generation coronary artery motion correction algorithm (MC1), and second-generation, whole-heart motion correction algorithm (MC2). The image quality of the origin of left coronary, right coronary, aortic valve, pulmonary valve, mitral valve, tricuspid valve, aorta root, pulmonary artery root, ventricular septum (VS), and atrial septum (AS) was assessed by 2 experienced radiologists using a 4-point scale (1, nondiagnostic; 2, detectable; 3, measurable; and 4, excellent); nonparametric test was used to analyze and compare the differences among 3 groups; and post hoc multiple comparisons were used between different methods. There were group differences for cardiac structures except VS and AS, with MC2 having the best image quality and STD having the worst image quality. Post hoc multiple comparisons showed that MC2 was better than MC1 and STD in all structures except VS and AS where all 3 algorithms performed equally, whereas MC1 was better than STD only in the origin of left coronary, right coronary, and mitral valve. A second-generation, whole-heart motion correction algorithm further significantly improves cardiac image quality beyond the coronaries in CCTA for pediatric patients with high heart rates.

Deep Learning-Based Detection and Correction of Cardiac MR Motion Artefacts During Reconstruction for High-Quality Segmentation

Segmenting anatomical structures in medical images has been successfully addressed with deep learning methods for a range of applications. However, this success is heavily dependent on the quality of the image that is being segmented. A commonly neglected point in the medical image analysis community is the vast amount of clinical images that have severe image artefacts due to organ motion, movement of the patient and/or image acquisition related issues. In this paper, we discuss the implications of image motion artefacts on cardiac MR segmentation and compare a variety of approaches for jointly correcting for artefacts and segmenting the cardiac cavity. The method is based on our recently developed joint artefact detection and reconstruction method, which reconstructs high quality MR images from k-space using a joint loss function and essentially converts the artefact correction task to an under-sampled image reconstruction task by enforcing a data consistency term. In this paper, we propose to use a segmentation network coupled with this in an end-to-end framework. Our training optimises three different tasks: 1) image artefact detection, 2) artefact correction and 3) image segmentation. We train the reconstruction network to automatically correct for motion-related artefacts using synthetically corrupted cardiac MR k-space data and uncorrected reconstructed images. Using a test set of 500 2D+time cine MR acquisitions from the UK Biobank data set, we achieve demonstrably good image quality and high segmentation accuracy in the presence of synthetic motion artefacts. We showcase better performance compared to various image correction architectures.

Cross-scanning optical coherence tomography angiography for eye motion correction.

We propose a cross-scanning optical coherence tomography (CS-OCT) system to correct eye motion artifacts in OCT angiography images. This system employs a dual-illumination configuration with two orthogonally polarized beams, each of which simultaneously perform raster scanning in perpendicular direction with each other over the same area. In the reference arm, a polarization delay unit is used to acquire the two orthogonally polarized interferograms with a single photo detector by introducing different optical delay lines. The two cross-scanned volume data are affected by the same eye motion but in two orthogonal directions. We developed a motion correction algorithm, which removes artifacts in the slow axis of each angiogram using the other and merges them through a nonrigid registration algorithm. In this manner, we obtained a motion-corrected angiogram within a single volume scanning time without additional eye-tracking devices.

Impact of motion artefacts and motion-artefact correction on diagnostic accuracy of apical periodontitis in CBCT images: an ex vivo study in human cadavers.

To assess the impact of motion artefacts and motion-artefact correction on diagnostic accuracy of apical periodontitis (AP) in CBCT images. Based on clinical and radiographic inspection of 40 formalin-fixated human jaw specimens, 77 roots in 45 teeth (molars and premolars), with various disease and treatment state, were selected. The specimens were mounted on a robot simulating 3-mm movement types (nodding, lateral rotation and tremor). CBCT images with and without (controls) movements were acquired in four CBCT units: without motion-artefact correction in Cranex 3Dx, Orthophos SL 3D, and Promax 3D Mid, and with motion-artefact correction in Promax 3D Mid and X1. Three observers blindly assessed (i) whether the images were interpretable and (ii) if AP was present (5-step probability index). Histopathology provided the reference standard for presence of AP. Weighted Kappa statistics described inter-observer agreement. Estimates of diagnostic accuracy were assessed by means of receiver operator characteristic (ROC) curve analysis. Area under the curve (AUC) provided a measure of accuracy, and paired-sample AUC difference tests compared differences amongst the CBCT units and movement types. Observer agreement was substantial for control images, moderate for motion-artefact corrected images and fair for images without motion-artefact correction. When movement was present, motion-artefact correction reduced the percentage of images scored as noninterpretable or with uncertain disease state (score 3 in the 5-step probability index). Control images were not perfectly accurate (both false-positive and false-negative results were present; AUC 0.750-0.799). Images acquired with movement and without motion-artefact correction (AUC 0.541-0.709) were associated with significantly lower accuracy than control images (P<0.05). With motion-artefact correction, accuracy was comparable to that observed in control images (AUC 0.732-0.790). Diagnostic accuracy of apical periodontitis in CBCT images was dependent on the presence of motion artefacts (i.e. lower accuracy associated with the presence of movement). Motion-artefact correction systems positively influenced image interpretability and diagnostic accuracy.

Real-time 3D movement correction for two-photon imaging in behaving animals.

Two-photon microscopy is widely used to investigate brain function across multiple spatial scales. However, measurements of neural activity are compromised by brain movement in behaving animals. Brain motion-induced artifacts are typically corrected using post hoc processing of two-dimensional images, but this approach is slow and does not correct for axial movements. Moreover, the deleterious effects of brain movement on high-speed imaging of small regions of interest and photostimulation cannot be corrected post hoc. To address this problem, we combined random-access three-dimensional (3D) laser scanning using an acousto-optic lens and rapid closed-loop field programmable gate array processing to track 3D brain movement and correct motion artifacts in real time at up to 1 kHz. Our recordings from synapses, dendrites and large neuronal populations in behaving mice and zebrafish demonstrate real-time movement-corrected 3D two-photon imaging with submicrometer precision.

In vivo noninvasive measurement of spatially resolved corneal elasticity in human eyes using Lamb wave optical coherence elastography.

Current elastography techniques are limited in application to accurately assess spatially resolved corneal elasticity in vivo for human eyes. The air-puff optical coherence elastography (OCE) with an eye motion artifacts correction algorithm is developed to distinguish the in vivo cornea vibration from the eye motion and visualize the Lamb wave propagation clearly in healthy subjects. Based on the Lamb wave model, the phase velocity dispersion curve in the high-frequency is calculated to obtain spatially resolved corneal elasticity accurately with high repeatability. It is found that the corneal elasticity has regional variations and is correlated with intraocular pressure, which suggests that the method has the potential to provide noninvasive measurement of spatially resolved corneal elasticity in clinical practice.

Correction of Motion Artifacts Using a Multiscale Fully Convolutional Neural Network.

Motion artifacts are a frequent source of image degradation in the clinical application of MR imaging (MRI). Here we implement and validate an MRI motion-artifact correction method using a multiscale fully convolutional neural network. The network was trained to identify motion artifacts in axial T2-weighted spin-echo images of the brain. Using an extensive data augmentation scheme and a motion artifact simulation pipeline, we created a synthetic training dataset of 93,600 images based on only 16 artifact-free clinical MRI cases. A blinded reader study using a unique test dataset of 28 additional clinical MRI cases with real patient motion was conducted to evaluate the performance of the network. Application of the network resulted in notably improved image quality without the loss of morphologic information. For synthetic test data, the average reduction in mean squared error was 41.84%. The blinded reader study on the real-world test data resulted in significant reduction in mean artifact scores across all cases (P < .03). Retrospective correction of motion artifacts using a multiscale fully convolutional network is promising and may mitigate the substantial motion-related problems in the clinical MRI workflow.

Deep Learning Cross-Phase Style Transfer for Motion Artifact Correction in Coronary Computed Tomography Angiography

Motion artifacts may occur in coronary computed tomography angiography (CCTA) due to the heartbeat and impede the clinician's diagnosis of coronary arterial diseases. Thus, motion artifact correction of the coronary artery is required to quantify the risk of disease more accurately. We present a novel method based on deep learning for motion artifact correction in CCTA. Because the image of the coronary artery without motion (the ground-truth data required in supervised deep learning) is medically unattainable, we apply a style transfer method to 2D image patches cropped from full-phase 4D computed tomography (CT) to synthesize these images. We then train a convolutional neural network (CNN) for motion artifact correction using this synthetic ground-truth (SynGT). During testing, the output motion-corrected 2D image patches of the trained network are reinserted into the 3D CT volume with volumetric interpolation. The proposed method is evaluated using both phantom and clinical data. A phantom study demonstrates comparable results to other methods in quantitative performance and outperforms those methods in computation time. For clinical data, a quantitative analysis based on metric measurements is presented that confirms the correction of motion artifacts. Moreover, an observer study finds that by applying the proposed method, motion artifacts are markedly reduced, and boundaries of the coronary artery are much sharper, with a strong inter-observer agreement (κ = 0.78). Finally, evaluations using commercial software on the original and resulting CT volumes of the proposed method reveal a considerable increase in tracked coronary artery length.

Numerical method for axial motion artifact correction in retinal spectral-domain optical coherence tomography.

A numerical method that compensates image distortions caused by random fluctuations of the distance to an object in spectral-domain optical coherence tomography (SD OCT) has been proposed and verified experimentally. The proposed method is based on the analysis of the phase shifts between adjacent scans that are caused by micrometer-scale displacements and the subsequent compensation for the displacements through phase-frequency correction in the spectral space. The efficiency of the method is demonstrated in model experiments with harmonic and random movements of a scattering object as well as during in vivo imaging of the retina of the human eye.

MedGAN: Medical image translation using GANs

Image-to-image translation is considered a new frontier in the field of medical image analysis, with numerous potential applications. However, a large portion of recent approaches offers individualized solutions based on specialized task-specific architectures or require refinement through non-end-to-end training. In this paper, we propose a new framework, named MedGAN, for medical image-to-image translation which operates on the image level in an end-to-end manner. MedGAN builds upon recent advances in the field of generative adversarial networks (GANs) by merging the adversarial framework with a new combination of non-adversarial losses. We utilize a discriminator network as a trainable feature extractor which penalizes the discrepancy between the translated medical images and the desired modalities. Moreover, style-transfer losses are utilized to match the textures and fine-structures of the desired target images to the translated images. Additionally, we present a new generator architecture, titled CasNet, which enhances the sharpness of the translated medical outputs through progressive refinement via encoder-decoder pairs. Without any application-specific modifications, we apply MedGAN on three different tasks: PET-CT translation, correction of MR motion artefacts and PET image denoising. Perceptual analysis by radiologists and quantitative evaluations illustrate that the MedGAN outperforms other existing translation approaches.

In-vivo 3D corneal elasticity using air-coupled ultrasound optical coherence elastography.

Corneal elasticity can resist elastic deformations under intraocular pressure to maintain normal corneal shape, which has a great influence on corneal refractive function. Elastography can measure tissue elasticity and provide a powerful tool for clinical diagnosis. Air-coupled ultrasound optical coherence elastography (OCE) has been used in the quantification of ex-vivo corneal elasticity. However, in-vivo imaging of the cornea remains a challenge. The 3D air-coupled ultrasound OCE with an axial motion artifacts correction algorithm was developed to distinguish the in-vivo cornea vibration from the axial eye motion in anesthetized rabbits and visualize the elastic wave propagation clearly. The elastic wave group velocity of in-vivo rabbit cornea was measured to be 5.96 ± 0.55 m/s, which agrees with other studies. The results show the potential of 3D air-coupled ultrasound OCE with an axial motion artifacts correction algorithm for quantitative in-vivo assessment of corneal elasticity.

Quantitative three-dimensional ultrashort echo time cones imaging of the knee joint with motion correction.

Knee degeneration involves all the major tissues in the joint. However, conventional MRI sequences can only detect signals from long T2 tissues such as the superficial cartilage, with little signal from the deep cartilage, menisci, ligaments, tendons and bone. It is highly desirable to develop new sequences that can detect signal from all major tissues in the knee. We aimed to develop a comprehensive quantitative three-dimensional ultrashort echo time (3D UTE) cones imaging protocol for a truly "whole joint" evaluation of knee degeneration. The protocol included 3D UTE cones actual flip angle imaging (3D UTE-Cones-AFI) for T1 mapping, multiecho UTE-Cones with fat suppression for T2 * mapping, UTE-Cones with adiabatic T1ρ (AdiabT1ρ ) preparation for AdiabT1ρ mapping, and UTE-Cones magnetization transfer (UTE-Cones-MT) for MT ratio (MTR) and modeling of macromolecular proton fraction (f). An elastix registration technique was used to compensate for motion during scans. Quantitative data analyses were performed on the registered data. Three knee specimens and 15 volunteers were evaluated at 3T. The elastix motion correction algorithm worked well in correcting motion artifacts associated with relatively long scan times. Much improved curve fitting was achieved for all UTE-Cones biomarkers with greatly reduced root mean square errors. The averaged T1 , T2 *, AdiabT1ρ , MTR and f for knee joint tissues of 15 healthy volunteers were reported. The 3D UTE-Cones quantitative imaging techniques (ie, T1 , T2 *, AdiabT1ρ , MTR and MT modeling) together with elastix motion correction provide robust volumetric measurement of relaxation times, MTR and f of both short and long T2 tissues in the knee joint.

Precise measurement of coronary stenosis diameter with CCTA using CT number calibration.

Coronary x-ray computed tomography angiography (CCTA) continues to develop as a noninvasive method for the assessment of coronary vessel geometry and the identification of physiologically significant lesions. The uncertainty of quantitative lesion diameter measurement due to limited spatial resolution and vessel motion reduces the accuracy of CCTA diagnoses. In this paper, we introduce a new technique called computed tomography (CT)-number-Calibrated Diameter to improve the accuracy of the vessel and stenosis diameter measurements with CCTA. A calibration phantom containing cylindrical holes (diameters spanning from 0.8mm through 4.0mm) capturing the range of diameters found in human coronary vessels was three-dimensional printed. We also printed a human stenosis phantom with 17 tubular channels having the geometry of lesions derived from patient data. We acquired CT scans of the two phantoms with seven different imaging protocols. Calibration curves relating vessel intraluminal maximum voxel value (maximum CT number of a voxel, described in Hounsfield Units, HU) to true diameter, and full-width-at-half maximum (FWHM) to true diameter were constructed for each CCTA protocol. In addition, we acquired scans with a small constant motion (15mm/s) and used a motion correction reconstruction (Snapshot Freeze) algorithm to correct motion artifacts. We applied our technique to measure the lesion diameter in the 17 lesions in the stenosis phantom and compared the performance of CT-number-Calibrated Diameter to the ground truth diameter and a FWHM estimate. In all cases, vessel intraluminal maximum voxel value vs diameter was found to have a simple functional form based on the two-dimensional point spread function yielding a constant maximum voxel value region above a cutoff diameter, and a decreasing maximum voxel value vs decreasing diameter below a cutoff diameter. After normalization, focal spot size and reconstruction kernel were the principal determinants of cutoff diameter and the rate of maximum voxel value reduction vs decreasing diameter. The small constant motion had a significant effect on the CT number calibration; however, the motion-correction algorithm returned the maximum voxel value vs diameter curve to that of stationary vessels. The CT number Calibration technique showed better performance than FWHM estimation of diameter, yielding a high accuracy in the tested range (0.8mm through 2.5mm). We found a strong linear correlation between the smallest diameter in each of 17 lesions measured by CT-number-Calibrated Diameter (DC ) and ground truth diameter (Dgt ), (DC =0.951×Dgt +0.023mm, r=0.998 with a slope very close to 1.0 and intercept very close to 0mm. Computed tomography-number-Calibrated Diameter is an effective method to enhance the accuracy of the estimate of small vessel diameters and degree of coronary stenosis in CCTA.

Deep-learning-based motion-correction algorithm in optical resolution photoacoustic microscopy

In this study, we propose a deep-learning-based method to correct motion artifacts in optical resolution photoacoustic microscopy (OR-PAM). The method is a convolutional neural network that establishes an end-to-end map from input raw data with motion artifacts to output corrected images. First, we performed simulation studies to evaluate the feasibility and effectiveness of the proposed method. Second, we employed this method to process images of rat brain vessels with multiple motion artifacts to evaluate its performance for in vivo applications. The results demonstrate that this method works well for both large blood vessels and capillary networks. In comparison with traditional methods, the proposed method in this study can be easily modified to satisfy different scenarios of motion corrections in OR-PAM by revising the training sets.

Impact of movement and motion-artefact correction on image quality and interpretability in CBCT units with aligned and lateral-offset detectors.

To evaluate the impact of movement and motion-artefact correction systems on CBCT image quality and interpretability of simulated diagnostic tasks for aligned and lateral-offset detectors. A human skull simulating three diagnostic tasks (implant planning in the anterior maxilla, implant planning in the left-side-mandible and mandibular molar furcation assessment in the right-side-mandible) was mounted on a robot performing six movement types. Four CBCT units were used: Cranex 3Dx (CRA), Ortophos SL (ORT), Promax 3D Mid (PRO), and X1. Protocols were tested with aligned (CRA, ORT, PRO, and X1) and lateral-offset (CRA and PRO) detectors and two motion-artefact correction systems (PRO and X1). Movements were performed at one moment-in-time (t1), for units with an aligned detector, and three moments-in-time (t1-first-half of the acquisition, t2-second-half, t3-both) for the units with a lateral-offset detector. 98 volumes were acquired. Images were scored by three observers, blinded to the unit and presence of movement, for motion-related stripe artefacts, overall unsharpness, and interpretability. Fleiss' κ was used to assess interobserver agreement. Interobserver agreement was substantial for all parameters (0.66-0.68). For aligned detectors, in all diagnostic tasks a motion-artefact correction system influenced image interpretability. For lateral-offset detectors, the interpretability varied according to the unit and moment-in-time, in which the movement was performed. PRO motion-artefact correction system was less effective for the offset detector than its aligned counterpart. Motion-artefact correction systems enhanced image quality and interpretability for units with aligned detectors but were less effective for those with lateral-offset detectors.

Influence of virtual monochromatic spectral image at different energy levels on motion artifact correction in dual-energy spectral coronary CT angiography.

To investigate the influence of virtual monochromatic spectral (VMS) CT images at different energy levels on the effectiveness of a motion correction technique (SSF) in dual-energy Spectral coronary CT angiography (CCTA). 29 cases suspected of or diagnosed with coronary artery disease underwent Spectral CCTA using a prospective ECG triggering with 250ms padding time. SSF was applied to the determined least-motion phase to generate 6 additional sets of VMS images with energy levels from 40 to 100keV. CT value and standard deviation (SD) in the aortic root and epicardial adipose tissue were measured. Image quality of the RCA, LAD and LCX was evaluated on a per-vessel basis in each patient. Two reviewers evaluated the artery using the score of the segment. The low energy VMS images increased CT value and image noise compared with higher-energy VMS images, except 90keV and 100keV. The CNR of 40-70keV were higher than those of 80-100keV (P < 0.05). The image quality scores for images at 50-80keV were higher than those of 40, 90, and 100keV (P < 0.05), and the VMS image quality at 50keV and 60keV with SSF was the highest. SSF can effectively reduce the motion artifacts when coronary vessels have suitable contrast enhancement which can be achieved by adjusting energy levels of VMS images.

Review on Retrospective Procedures to Correct Retinal Motion Artefacts in OCT Imaging

Motion artefacts from involuntary changes in eye fixation remain a major imaging issue in optical coherence tomography (OCT). This paper reviews the state-of-the-art of retrospective procedures to correct retinal motion and axial eye motion artefacts in OCT imaging. Following an overview of motion induced artefacts and correction strategies, a chronological survey of retrospective approaches since the introduction of OCT until the current days is presented. Pre-processing, registration, and validation techniques are described. The review finishes by discussing the limitations of the current techniques and the challenges to be tackled in future developments.

Dynamic FDG-PET/CT in the Initial Staging of Primary Breast Cancer: Clinicopathological Correlations

Our aim was to evaluate correlation between clinicopathological features (clinical T and clinical N stages; histological type; nuclear grade; hormone-receptor and HER2 status, proliferation activity and tumor subtypes) of breast cancer and kinetic parameters measured by staging dynamic FDG-PET/CT examinations. Following ethical approval and patients’ informed consent we included 34 patients with 35 primary breast cancers in our prospective study. We performed dynamic PET imaging, and assessed plasma activity noninvasively. To delineate primary tumors we applied a frame-by-frame semi-automatic software-based correction of motion artefacts. FDG two-compartment kinetic modelling was applied to assess K1, k2, k3 rate coefficients and to calculate Ki (tracer flux constant) and MRFDG (FDG metabolic rate). We found that k3, Ki and MRFDG were significantly higher in higher grade (p = 0.0246, 0.0089 and 0.0076, respectively), progesterone-receptor negative (p = 0.0344, 0.0217 and 0.0132) and highly-proliferating (p = 0.0414, 0.0193 and 0.0271) tumors as well as in triple-negative and hormone-receptor negative/HER2-positive subtypes (p = 0.0310, 0.0280 and 0.0186). Ki and MRFDG were significantly higher in estrogen-receptor negative tumors (p = 0.0300 and 0.0247, respectively). Ki was significantly higher in node-positive than in node-negative disease (p = 0.0315). None of the assessed FDG-kinetic parameters showed significant correlation with stromal TIL. In conclusion, we confirmed a significant relationship between kinetic parameters measured by dynamic PET and the routinely assessed clinicopathological factors of breast cancer: high-grade, hormone-receptor negative tumors with high proliferation rate are characterized by higher cellular FDG-uptake and FDG-phosphorylation rate. Furthermore, we found that kinetic parameters based on the dynamic examinations are probably not influenced by stromal TIL infiltration.

Fetal MRI and prenatal diagnosis of congenital heart defects

Fetal MRI and prenatal diagnosis of congenital heart defects

Comparison of different motion correction techniques for dynamic FDG-PET/CT studies in breast cancer patients.

Our aim was to evaluate interchangeability of different motion correction methods in the assessment of dynamic FDG-PET/CT studies in breast cancer patients as well as to assess the interrater reliability of these methods. In our prospective study we included patients with malignant breast tumours. Dynamic PET acquisition lasted for 60 minutes after tracer (FDG) injection. Every study was assessed by the same two experienced observers. We assessed plasma activity noninvasively. In case of the primary tumour VOIs we applied two different approaches to correct motion artefacts: method I) frame-by-frame manual motion correction; method II) frame-by-frame semi-automatic software-based motion correction. FDG two-compartment kinetic modelling was applied to assess K<inf>1</inf>, k<inf>2</inf>, k<inf>3</inf> rate coefficients and to calculate K<inf>i</inf> (tracer flux constant) and MRFDG (FDG metabolic rate). Thirty-five lesions detected during 34 dynamic studies were included in this current analysis. Interrater reliability of both applied motion correction methods proved to be excellent (ICC=0.89-0.99), except K<inf>i</inf> measured by method I (ICC=0.66). Bland-Altman analysis revealed that method II resulted in significantly lower values than method I regarding k<inf>3</inf> and K<inf>i</inf> in case of both observers, and regarding MRFDG in one of the observers. In case of K<inf>1</inf> and k<inf>2</inf> the two methods were in good agreement. Both applied methods proved to be reproducible and reliable, especially method II, where every measured kinetic parameter showed excellent interrater reliability. Different approaches of motion correction could have a significant effect on the results of the kinetic modelling; therefore careful selection of the most reliable method is advised.