Movement correction in DCE-MRI through windowed and reconstruction dynamic mode decomposition

Dynamic Mode Decomposition of Multiphoton and Stimulated Emission Depletion Microscopy Data for Analysis of Fluorescent Probes in Cellular Membranes

An analysis of the membrane organization and intracellular trafficking of lipids often relies on multiphoton (MP) and super-resolution microscopy of fluorescent lipid probes. A disadvantage of particularly intrinsically fluorescent lipid probes, such as the cholesterol and ergosterol analogue, dehydroergosterol (DHE), is their low MP absorption cross-section, resulting in a low signal-to-noise ratio (SNR) in live-cell imaging. Stimulated emission depletion (STED) microscopy of membrane probes like Nile Red enables one to resolve membrane features beyond the diffraction limit but exposes the sample to a lot of excitation light and suffers from a low SNR and photobleaching. Here, dynamic mode decomposition (DMD) and its variant, higher-order DMD (HoDMD), are applied to efficiently reconstruct and denoise the MP and STED microscopy data of lipid probes, allowing for an improved visualization of the membranes in cells. HoDMD also allows us to decompose and reconstruct two-photon polarimetry images of TopFluor-cholesterol in model and cellular membranes. Finally, DMD is shown to not only reconstruct and denoise 3D-STED image stacks of Nile Red-labeled cells but also to predict unseen image frames, thereby allowing for interpolation images along the optical axis. This important feature of DMD can be used to reduce the number of image acquisitions, thereby minimizing the light exposure of biological samples without compromising image quality. Thus, DMD as a computational tool enables gentler live-cell imaging of fluorescent probes in cellular membranes by MP and STED microscopy.

Mobile Terminal Equipment and Methods of Martial Arts Movement Correction in Intelligent Physical Education Environment

In recent years, the physical quality of middle school students in China has generally declined, which has attracted the attention of the state and the Ministry of education. With the development of Internet technology, China's physical education teaching environment has gradually become intelligent. This article mainly studies the mobile terminal equipment and methods of martial arts movement correction in the intelligent physical education environment. 21 young martial arts athletes were selected as the research objects. In the experiment, functional screening (FMS) was used to test the martial arts athletes, followed by FMS tests and scores. A video camera was used to record the motion test from the subjects' sagittal and frontal planes. Using wireless sensor technology to collect the athletes' motion signals, after the twelfth week, the FMS, SEBT, and the number of successful routines were tested on the two groups of athletes, respectively. The pre-test data and the post-correction data of the two test indicators were compared and analyzed. There is no significant difference. The necessary statistics and integration of the obtained data are carried out by using the calculation methods in sports statistics. The experimental data showed that the average total scores of FMS screening test of Changquan athletes and Taijiquan athletes were 14.71 ± 1.52 and 16.20 ± 1.32, respectively. The results of the research on the mobile terminal equipment and methods of martial arts movement correction in the intelligent sports environment show that the mobile terminal equipment can improve the independent training ability of athletes, and at the same time has a good correction effect on irregular movements.

Motion correction of free-breathing magnetic resonance renography using model-driven registration

INTRODUCTION

Model-driven registration (MDR) is a general approach to remove patient motion in quantitative imaging. In this study, we investigate whether MDR can effectively correct the motion in free-breathing MR renography (MRR).

MATERIALS AND METHODS

MDR was generalised to linear tracer-kinetic models and implemented using 2D or 3D free-form deformations (FFD) with multi-resolution and gradient descent optimization. MDR was evaluated using a kidney-mimicking digital reference object (DRO) and free-breathing patient data acquired at high temporal resolution in multi-slice 2D (5 patients) and 3D acquisitions (8 patients). Registration accuracy was assessed using comparison to ground truth DRO, calculating the Hausdorff distance (HD) between ground truth masks with segmentations and visual evaluation of dynamic images, signal-time courses and parametric maps (all data).

RESULTS

DRO data showed that the bias and precision of parameter maps after MDR are indistinguishable from motion-free data. MDR led to reduction in HD (HD_unregistered = 9.98 ± 9.76, HD_registered = 1.63 ± 0.49). Visual inspection showed that MDR effectively removed motion effects in the dynamic data, leading to a clear improvement in anatomical delineation on parametric maps and a reduction in motion-induced oscillations on signal-time courses.

DISCUSSION

MDR provides effective motion correction of MRR in synthetic and patient data. Future work is needed to compare the performance against other more established methods.