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Usage of Methotrexate in Gynecologic and Obstetric Training: Just what the Radiologist Needs to Understand.
Change detection has received extensive attention because of its realistic significance and broad application fields. However, none of the existing change detection algorithms can handle all scenarios and tasks so far. Different from the most of contributions from the research community in recent years, this paper does not work on designing new change detection algorithms. We, instead, solve the problem from another perspective by enhancing the raw detection results after change detection. As a result, the proposed method is applicable to various kinds of change detection methods, and regardless of how the results are detected. In this paper, we propose Fast Spatiotemporal Tree Filter (FSTF), a purely unsupervised detection method, to enhance coarse binary detection masks obtained by different kinds of change detection methods. In detail, the proposed FSTF has adopted a volumetric structure to effectively synthesize spatiotemporal information of the same target from the current time and history frames to enhance detection. The computational complexity analyzed in the view of graph theory also show that the fast realization of FSTF is a linear time algorithm, which is capable of handling efficient on-line detection tasks. Finally, comprehensive experiments based on qualitative and quantitative analysis verify that FSTF-based change detection enhancement is superior to several other state-of-the-art methods including fully connected Conditional Random Field (CRF), joint bilateral filter, and guided filter. It is illustrated that FSTF is versatile enough to also improve saliency detection as well as semantic image segmentation.Degree of anisotropy (DoA) of mechanical properties has been assessed as the ratio of acoustic radiation force impulse (ARFI)-induced peak displacements (PDs) achieved using spatially asymmetric point spread functions (PSFs) that are rotated 90° to each other. Such PSF rotation has been achieved by manually rotating a linear array transducer, but manual rotation is cumbersome and prone to misalignment errors and higher variability in measurements. The purpose of this work is to evaluate the feasibility of electronic PSF rotation using a three-row transducer, which will reduce variability in DoA assessment. PIN1 inhibitor API-1 manufacturer A Siemens 9L4, with 3×192 elements, was simulated in Field II to generate spatially asymmetric ARFI PSFs that were electronically rotated 63° from each other. Then, using the finite element method (FEM), PD due to the ARFI excitation PSFs in 42 elastic, incompressible, transversely isotropic (TI) materials with shear moduli ratios of 1.0-6.0 were modeled. Finally, the ratio of PDs achieved using the two rotated PSFs was evaluated to assess elastic DoA. DoA increased with increasing shear moduli ratios and distinguished materials with 17% or greater difference in shear moduli ratios (Wilcoxon, ). Experimentally, the ratio of PDs achieved using ARFI PSF rotated 63° from each other distinguished the biceps femoris muscle from two pigs, which had median shear moduli ratios of 4.25 and 3.15 as assessed by shear wave elasticity imaging (SWEI). These results suggest that ARFI-based DoA assessment can be achieved without manual transducer rotation using a three-row transducer capable of electronically rotating PSFs by 63°. It is expected that electronic PSF rotation will facilitate data acquisitions and improve the reproducibility of elastic anisotropy assessments.This study evaluates the performance of an acoustic radiation force impulse (ARFI)-based outcome parameter, the decadic logarithm of the variance of acceleration, or log(VoA), for measuring carotid fibrous cap thickness. Carotid plaque fibrous cap thickness measurement by log(VoA) was compared to that by ARFI peak displacement (PD) in patients undergoing clinically indicated carotid endarterectomy using a spatially-matched histological validation standard. Fibrous caps in parametric log(VoA) and PD images were automatically segmented using a custom clustering algorithm, and a pathologist with expertise in atherosclerosis hand-delineated fibrous caps in histology. Over 10 fibrous caps, log(VoA)-derived thickness was more strongly correlated to histological thickness than PD-derived thickness, with Pearson correlation values of 0.98 for log(VoA) compared to 0.89 for PD. The log(VoA)-derived cap thickness also had better agreement with histology-measured thickness, as assessed by the concordance correlation coefficient (0.95 versus 0.62), and, by Bland-Altman analysis, was more consistent than PD-derived fibrous cap thickness. These results suggest that ARFI log(VoA) enables improved discrimination of fibrous cap thickness relative to ARFI PD and further contributes to the growing body of evidence demonstrating ARFI's overall relevance to delineating the structure and composition of carotid atherosclerotic plaque for stroke risk prediction.The phased-array radio frequency (RF) coil plays a vital role in magnetic resonance-guided focused ultrasound (MRgFUS) neuromodulation studies, where accurate brain functional stimulations and neural circuit observations are required. Although various designs of phased-array coils have been reported, few are suitable for ultrasound stimulations. In this study, an MRgFUS neuromodulation system comprised of a whole brain coverage non-human primate (NHP) RF coil and an MRI-compatible ultrasound device was developed. When compared to a single loop coil, the NHP coil provided up to a 50% increase in the signal-to-noise ratio (SNR) in the brain and acquired better anatomical image-quality. The NHP coil also demonstrated the ability to achieve higher spatial resolution and reduce distortion in echo-planer imaging (EPI). Ultrasound beam characteristics and transcranial magnetic resonance acoustic radiation force (MR-ARF) were measured for simulated positions, and calculated B0 maps were employed to establish MRI-compatibility. The differences between focused off and on ultrasound techniques were measured using SNR, g-factors, and temporal SNR (tSNR) analyses and all deviations were under 2.3%. The EPI images quality and stable tSNR demonstrated the suitability of the MRgFUS neuromodulation system to conduct functional MRI studies. Last, the time course of the blood oxygen level dependent (BOLD) signal of posterior cingulate cortex in a focused ultrasound neuromodulation study was detected and repeated with MR thermometry.
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