Discerning nonrigid 3D shapes from motion cues.
Ontology highlight
ABSTRACT:
SUBMITTER: Jain A
PROVIDER: S-EPMC3029717 | biostudies-literature | 2011 Jan
REPOSITORIES: biostudies-literature
Publications
Discerning nonrigid 3D shapes from motion cues.
Proceedings of the National Academy of Sciences of the United States of America 20110104 4
Many organisms and objects deform nonrigidly when moving, requiring perceivers to separate shape changes from object motions. Surprisingly, the abilities of observers to correctly infer nonrigid volumetric shapes from motion cues have not been measured, and structure from motion models predominantly use variants of rigidity assumptions. We show that observers are equally sensitive at discriminating cross-sections of flexing and rigid cylinders based on motion cues, when the cylinders are rotated ...[more]
Similar Datasets
Project description:PurposeTo develop an accelerated and nonrigid motion-compensated technique for efficient isotropic 3D whole-heart coronary magnetic resonance angiography (CMRA) with Cartesian acquisition.MethodsHighly efficient whole-heart 3D CMRA was achieved by combining image reconstruction from undersampled data using compressed sensing (CS) with a nonrigid motion compensation framework. Undersampled acquisition was performed using a variable-density Cartesian trajectory with radial order (VD-CAPR). Motion correction was performed in two steps: beat-to-beat 2D translational correction with motion estimated from interleaved image navigators, and bin-to-bin 3D nonrigid correction with motion estimated from respiratory-resolved images reconstructed from undersampled 3D CMRA data using CS. Nonrigid motion fields were incorporated into an undersampled motion-compensated reconstruction, which combines CS with the general matrix description formalism. The proposed approach was tested on 10 healthy subjects and compared against a conventional twofold accelerated 5-mm navigator-gated and tracked acquisition.ResultsThe proposed method achieves isotropic 1.2-mm Cartesian whole-heart CMRA in 5 min ± 1 min (~8× acceleration). The proposed approach provides good-quality images of the left and right coronary arteries, comparable to those of a twofold accelerated navigator-gated and tracked acquisition, but scan time was up to about four times faster. For both coronaries, no significant differences (P > 0.05) in vessel sharpness and length were found between the proposed method and reference scan.ConclusionThe feasibility of a highly efficient motion-compensated reconstruction framework for accelerated 3D CMRA has been demonstrated in healthy subjects. Further investigation is required to assess the clinical value of the method.
| S-EPMC5814733 | biostudies-literature
Project description:PurposeTo develop a respiratory motion correction framework to accelerate free-breathing three-dimensional (3D) whole-heart coronary lumen and coronary vessel wall MRI.MethodsWe developed a 3D flow-independent approach for vessel wall imaging based on the subtraction of data with and without T2-preparation prepulses acquired interleaved with image navigators. The proposed method corrects both datasets to the same respiratory position using beat-to-beat translation and bin-to-bin nonrigid corrections, producing coregistered, motion-corrected coronary lumen and coronary vessel wall images. The proposed method was studied in 10 healthy subjects and was compared with beat-to-beat translational correction (TC) and no motion correction for the left and right coronary arteries. Additionally, the coronary lumen images were compared with a 6-mm diaphragmatic navigator gated and tracked scan.ResultsNo significant differences (P > 0.01) were found between the proposed method and the gated and tracked scan for coronary lumen, despite an average improvement in scan efficiency to 96% from 59%. Significant differences (P < 0.01) were found in right coronary artery vessel wall thickness, right coronary artery vessel wall sharpness, and vessel wall visual score between the proposed method and TC.ConclusionThe feasibility of a highly efficient motion correction framework for simultaneous whole-heart coronary lumen and vessel wall has been demonstrated. Magn Reson Med 77:1894-1908, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
| S-EPMC5412916 | biostudies-literature
Project description:Nonrigid materials such as liquids or smoke deform over time. Little is known about the visual perception of nonrigid motion other than that many motion cues associated with rigid motion perception are not reliable for nonrigid motion. Nonrigid motion patterns lack clear borders and their movement can be inconsistent with the motion of their parts. We developed a novel stimulus that creates a nonrigid vortex motion pattern in a random dot distribution and decouples the movement of the vortex from the first-order motion of the dots. We presented three moving vortices that entailed consecutively fewer motion cues, eliminating occlusion, motion borders, and velocity field gradients in the process. Subjects were well able to report the end position and travel path in all cases, showing that nonrigid motion is perceived through an analysis of the temporal evolution of visual motion patterns and does not require borders or speed differences. Adding a coherent global motion did not hamper perception, but adding local noise did, indicating that the visual system uses mid-level features that are on a local scale. We also found that participants judged the movement of the nonrigid motion patterns slower than a rigid control, revealing that speed perception was based on a combination of motion of the parts and movement of the pattern. We propose that the visual system uses the temporal evolution of a motion pattern for the perception of nonrigid motion and suggest a plausible mechanism based on the curl of the motion field.
| S-EPMC9896959 | biostudies-literature
Project description:PURPOSE:To provide nonrigid respiratory motion-corrected DCE-MRI images with isotropic resolution of 1.5 mm, full coverage of abdomen, and covering the entire uptake curve with a temporal resolution of 6 seconds, for the quantitative assessment of hepatic lesions. METHODS:3D DCE-MRI data were acquired at 3 T during free breathing for 5 minutes using a 3D T1 -weighted golden-angle radial phase-encoding sequence. Nonrigid respiratory motion information was extracted and used in motion-corrected image reconstruction to obtain high-quality DCE-MRI images with temporal resolution of 6 seconds and isotropic resolution of 1.5 mm. An extended Tofts model was fitted to the dynamic data sets, yielding quantitative parametric maps of endothelial permeability using the hepatic artery as input function. The proposed approach was evaluated in 11 patients (52 ± 17 years, 5 men) with and without known hepatic lesions, undergoing DCE-MRI. RESULTS:Respiratory motion produced artifacts and misalignment between dynamic volumes (lesion average motion amplitude of 3.82 ± 1.11 mm). Motion correction minimized artifacts and improved average contrast-to-noise ratio of hepatic lesions in late phase by 47% (p < .01). Quantitative endothelial permeability maps of motion-corrected data demonstrated enhanced visibility of different pathologies (e.g., metastases, hemangiomas, cysts, necrotic tumor substructure) and showed improved contrast-to-noise ratio by 62% (p < .01) compared with uncorrected data. CONCLUSION:3D nonrigid motion correction in DCE-MRI improves both visual and quantitative assessment of hepatic lesions by ensuring accurate alignment between 3D DCE images and reducing motion blurring. This approach does not require breath-holds and minimizes scan planning by using a large FOV with isotropic resolution.
| S-EPMC6771884 | biostudies-other
Project description:Respiratory and cardiac motion is the most serious limitation to whole-body PET, resulting in spatial resolution close to 1 cm. Furthermore, motion-induced inconsistencies in the attenuation measurements often lead to significant artifacts in the reconstructed images. Gating can remove motion artifacts at the cost of increased noise. This paper presents an approach to respiratory motion correction using simultaneous PET/MRI to demonstrate initial results in phantoms, rabbits, and nonhuman primates and discusses the prospects for clinical application.Studies with a deformable phantom, a free-breathing primate, and rabbits implanted with radioactive beads were performed with simultaneous PET/MRI. Motion fields were estimated from concurrently acquired tagged MR images using 2 B-spline nonrigid image registration methods and incorporated into a PET list-mode ordered-subsets expectation maximization algorithm. Using the measured motion fields to transform both the emission data and the attenuation data, we could use all the coincidence data to reconstruct any phase of the respiratory cycle. We compared the resulting SNR and the channelized Hotelling observer (CHO) detection signal-to-noise ratio (SNR) in the motion-corrected reconstruction with the results obtained from standard gating and uncorrected studies.Motion correction virtually eliminated motion blur without reducing SNR, yielding images with SNR comparable to those obtained by gating with 5-8 times longer acquisitions in all studies. The CHO study in dynamic phantoms demonstrated a significant improvement (166%-276%) in lesion detection SNR with MRI-based motion correction as compared with gating (P < 0.001). This improvement was 43%-92% for large motion compared with lesion detection without motion correction (P < 0.001). CHO SNR in the rabbit studies confirmed these results.Tagged MRI motion correction in simultaneous PET/MRI significantly improves lesion detection compared with respiratory gating and no motion correction while reducing radiation dose. In vivo primate and rabbit studies confirmed the improvement in PET image quality and provide the rationale for evaluation in simultaneous whole-body PET/MRI clinical studies.
| S-EPMC4077320 | biostudies-literature
Project description:PurposeWith the recent introduction of the MR-LINAC, an MR-scanner combined with a radiotherapy LINAC, MR-based motion estimation has become of increasing interest to (retrospectively) characterize tumor and organs-at-risk motion during radiotherapy. To this extent, we introduce low-rank MR-MOTUS, a framework to retrospectively reconstruct time-resolved nonrigid 3D+t motion fields from a single low-resolution reference image and prospectively undersampled k-space data acquired during motion.TheoryLow-rank MR-MOTUS exploits spatiotemporal correlations in internal body motion with a low-rank motion model, and inverts a signal model that relates motion fields directly to a reference image and k-space data. The low-rank model reduces the degrees-of-freedom, memory consumption, and reconstruction times by assuming a factorization of space-time motion fields in spatial and temporal components.MethodsLow-rank MR-MOTUS was employed to estimate motion in 2D/3D abdominothoracic scans and 3D head scans. Data were acquired using golden-ratio radial readouts. Reconstructed 2D and 3D respiratory motion fields were, respectively, validated against time-resolved and respiratory-resolved image reconstructions, and the head motion against static image reconstructions from fully sampled data acquired right before and right after the motion.ResultsResults show that 2D+t respiratory motion can be estimated retrospectively at 40.8 motion fields per second, 3D+t respiratory motion at 7.6 motion fields per second and 3D+t head-neck motion at 9.3 motion fields per second. The validations show good consistency with image reconstructions.ConclusionsThe proposed framework can estimate time-resolved nonrigid 3D motion fields, which allows to characterize drifts and intra and inter-cycle patterns in breathing motion during radiotherapy, and could form the basis for real-time MR-guided radiotherapy.
| S-EPMC7839760 | biostudies-literature
Project description:Solution NMR spectroscopy can elucidate many features of the structure and dynamics of macromolecules, yet relaxation measurements, the most common source of experimental information on dynamics, can sample only certain ranges of dynamic rates. A complete characterization of motion of a macromolecule thus requires the introduction of complementary experimental approaches. Solid-state NMR spectroscopy successfully probes the time scale of nanoseconds to microseconds, a dynamic window where solution NMR results have been deficient, and probes conditions where the averaging effects of rotational diffusion of the molecule are absent. Combining the results of the two distinct techniques within a single framework provides greater insight into dynamics, but this task requires the common interpretation of results recorded under very different experimental conditions. Herein, we provide a unified description of dynamics that is robust to the presence of large-scale conformational exchange, where the diffusion tensor of the molecule varies on a time scale comparable to rotational diffusion in solution. We apply this methodology to the HIV-1 TAR RNA molecule, where conformational rearrangements are both substantial and functionally important. The formalism described herein is of greater generality than earlier combined solid-state/solution NMR interpretations, if detailed molecular structures are available, and can offer a more complete description of RNA dynamics than either solution or solid-state NMR spectroscopy alone.
| S-EPMC3626457 | biostudies-literature
Project description:The aim of the current study was to develop a novel approach for 2D breath-hold cardiac cine imaging from a single heartbeat, by combining cardiac motion-corrected reconstructions and nonrigidly aligned patch-based regularization. Conventional cardiac cine imaging is obtained via motion-resolved reconstructions of data acquired over multiple heartbeats. Here, we achieve single-heartbeat cine imaging by incorporating nonrigid cardiac motion correction into the reconstruction of each cardiac phase, in conjunction with a motion-aligned patch-based regularization. The proposed Motion-Corrected CINE (MC-CINE) incorporates all acquired data into the reconstruction of each (motion-corrected) cardiac phase, resulting in a better posed problem than motion-resolved approaches. MC-CINE was compared with iterative sensitivity encoding (itSENSE) and Extra-Dimensional Golden Angle Radial Sparse Parallel (XD-GRASP) in 14 healthy subjects in terms of image sharpness, reader scoring (range: 1-5) and reader ranking (range: 1-9) of image quality, and single-slice left ventricular assessment. MC-CINE was significantly superior to both itSENSE and XD-GRASP using 20 heartbeats, two heartbeats, and one heartbeat. Iterative SENSE, XD-GRASP, and MC-CINE achieved a sharpness of 74%, 74%, and 82% using 20 heartbeats, and 53%, 66%, and 82% with one heartbeat, respectively. The corresponding results for reader scoring were 4.0, 4.7, and 4.9 with 20 heartbeats, and 1.1, 3.0, and 3.9 with one heartbeat. The corresponding results for reader ranking were 5.3, 7.3, and 8.6 with 20 heartbeats, and 1.0, 3.2, and 5.4 with one heartbeat. MC-CINE using a single heartbeat presented nonsignificant differences in image quality to itSENSE with 20 heartbeats. MC-CINE and XD-GRASP at one heartbeat both presented a nonsignificant negative bias of less than 2% in ejection fraction relative to the reference itSENSE. It was concluded that the proposed MC-CINE significantly improves image quality relative to itSENSE and XD-GRASP, enabling 2D cine from a single heartbeat.
| S-EPMC10909414 | biostudies-literature
Project description:PURPOSE:To present and assess an automatic nonrigid image registration framework that compensates motion in cardiac magnetic resonance imaging (MRI) perfusion series and auxiliary images acquired under a wide range of conditions to facilitate myocardial perfusion quantification. MATERIALS AND METHODS:Our framework combines discrete feature matching for large displacement estimation with a dense variational optical flow formulation in a multithreaded architecture. This framework was evaluated on 291 clinical subjects to register 1.5T and 3.0T steady-state free-precession (FISP) and fast low-angle shot (FLASH) dynamic contrast myocardial perfusion images, arterial input function (AIF) images, and proton density (PD)-weighted images acquired under breath-hold (BH) and free-breath (FB) settings. RESULTS:Our method significantly improved frame-to-frame appearance consistency compared to raw series, expressed in correlation coefficient (R2 ?=?0.996?±?3.735E-3 vs. 0.978?±?2.024E-2, P < 0.0001) and mutual information (3.823?±?4.098E-1 vs. 2.967?±?4.697E-1, P < 0.0001). It is applicable to both BH (R2 ?=?0.998?±?3.217E-3 vs. 0.990?±?7.527E-3) and FB (R2 ?=?0.995?±?3.410E-3 vs. 0.968?±?2.257E-3) paradigms as well as FISP and FLASH sequences. The method registers PD images to perfusion T1 series (9.70% max increase in R2 vs. no registration, P < 0.001) and also corrects motion in low-resolution AIF series (R2 ?=?0.987?±?1.180E-2 vs. 0.964?±?3.860E-2, P < 0.001). Finally, we showed the myocardial perfusion contrast dynamic was preserved in the motion-corrected images compared to the raw series (R2 ?=?0.995?±?6.420E-3). CONCLUSION:The critical step of motion correction prior to pixel-wise cardiac MR perfusion quantification can be performed with the proposed universal system. It is applicable to a wide range of perfusion series and auxiliary images with different acquisition settings. LEVEL OF EVIDENCE:3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1060-1072.
| S-EPMC5557713 | biostudies-literature
Project description:To develop a nonrigid motion estimation method that is robust to heterogeneous intensity inconsistencies amongst the image pairs or image sequence.Intensity and contrast variations, as in dynamic contrast enhanced magnetic resonance imaging, present a considerable challenge to registration methods based on general discrepancy metrics. In this study, the authors propose and validate a novel method that is robust to such variations by utilizing shape features. The geometry of interest (GOI) is represented with a flexible zero level set, segmented via well-behaved regularized optimization. The optimization energy drives the zero level set to high image gradient regions, and regularizes it with area and curvature priors. The resulting shape exhibits high consistency even in the presence of intensity or contrast variations. Subsequently, a multiscale nonrigid registration is performed to seek a regular deformation field that minimizes shape discrepancy in the vicinity of GOIs.To establish the working principle, realistic 2D and 3D images were subject to simulated nonrigid motion and synthetic intensity variations, so as to enable quantitative evaluation of registration performance. The proposed method was benchmarked against three alternative registration approaches, specifically, optical flow, B-spline based mutual information, and multimodality demons. When intensity consistency was satisfied, all methods had comparable registration accuracy for the GOIs. When intensities among registration pairs were inconsistent, however, the proposed method yielded pronounced improvement in registration accuracy, with an approximate fivefold reduction in mean absolute error (MAE = 2.25 mm, SD = 0.98 mm), compared to optical flow (MAE = 9.23 mm, SD = 5.36 mm), B-spline based mutual information (MAE = 9.57 mm, SD = 8.74 mm) and mutimodality demons (MAE = 10.07 mm, SD = 4.03 mm). Applying the proposed method on a real MR image sequence also provided qualitatively appealing results, demonstrating good feasibility and applicability of the proposed method.The authors have developed a novel method to estimate the nonrigid motion of GOIs in the presence of spatial intensity and contrast variations, taking advantage of robust shape features. Quantitative analysis and qualitative evaluation demonstrated good promise of the proposed method. Further clinical assessment and validation is being performed.
| S-EPMC3855165 | biostudies-other