4D flow cardiovascular magnetic resonance (CMR) enables visualization of complex blood flow and quantification of biomarkers for vessel wall disease, such as wall shear stress (WSS). Because of the inherently long acquisition times, many efforts have been made to accelerate 4D flow acquisitions, however, no detailed analysis has been made on the effect of Cartesian compressed sensing accelerated 4D flow CMR at different undersampling rates on quantitative flow parameters and WSS.
3ds Max 2011 Highly Compressed
However, no comprehensive evaluation has been made on how highly (prospectively) Cartesian undersampling with CS reconstruction in 4D flow CMR affects quantitative flow parameter estimates like WSS in vivo.
Our specific method of accelerating 4D flow CMR using pseudo-spiral Cartesian sampling is schematically depicted in Fig. 1. 3D k-space consists of two phase encoding directions (ky,kz) and one fully sampled frequency encoding (readout) direction (kx). In regular Cartesian sampling (ky,kz)-profiles (a combination of ky and kz coordinates) would be acquired line-by-line (Fig. 1a). Additionally, in traditional cine imaging each (ky,kz)-profile would be sampled multiple times during each heartbeat (regular profile change) to ensure complete filling of k-t-space and a fully sampled time dimension for each (ky,kz)-profile (Fig. 1b). However, highly undersampling k-space in a random order on a Cartesian grid is not preferred since it would involve large steps in k-space. Regular line-by-line undersampling would complicate interleaving k-space sampling of multiple cardiac frames.
We implemented a pseudo-spiral filling strategy which was proposed earlier by Liu and Saloner [20] and also used in a similar fashion in G-CASPR [21], VDRad [17], ROCK-MUSIC [22] and GOCART [23] to create a randomly undersampled k-t-space. The pseudo-spiral trajectory has a couple of advantages. First, it involves only small jumps in k-space thereby minimizing eddy current related artifacts. Secondly, the pseudo-spirals can be rotated in a tiny golden-angle fashion, which provides optimal incoherence and a variable density sampling pattern with a fully sampled center (Fig. 1c), which is highly beneficial for CS reconstruction. Finally, despite the pseudo-spiral acquisition, the k-space points are still located on a Cartesian grid (hence the name pseudo-spiral), as shown in Fig. 1d, which improves the reconstruction as no regridding interpolation is required.
The proposed method presents a noteworthy conceptual advance. It is a new discovery that the time-reversal matrix can be highly compressed in terms of illumination channel coverage. We found that it is not even necessary to know what the illumination channels were. These conceptual findings naturally led to the advances in practicality. In addition to the reduction of illumination channel coverage, there is no need to perform time-consuming pre-calibration to gain prior knowledge on illumination field. It is no longer necessary to concern the phase stability among the E-field images. This enabled us to use dynamically varying random speckle patterns for illumination, instead of laser beam scanning by carefully aligned scanning mirrors, which greatly simplifies the experimental setup. We also presented novel volumetric image processing algorithm that replaces previous depth-wise angular scanning with continuous depth scanning in conjunction with dynamic speckle illuminations. We introduced the depth-correction step where all E-field images taken at different depths within the coherence length of the light source were numerically propagated to the target depth. This increases the number of images to be used for constructing a time-reversal matrix at each target depth, which effectively increases the volumetric imaging speed.
All these benefits of using the compressed time-reversal matrix come with a price to pay. A finite overlap between random illumination channels introduces additive noise in addition to multiple scattering noise. Therefore, achievable imaging depth is reduced relative to the full sampling by the amount of sparse sampling-induced noise. Using orthogonal illumination channels such as the Hadamard patterns instead of unknown speckles can minimize the sparse sampling-induced noise at the expense of hardware simplicity. In case when a priori knowledge of the scene is known, the number of required measurements could be drastically reduced by introducing a learned sensing approach29,30 using optimized illumination channels. Another drawback is that the achievable imaging resolution with the CTR-CLASS algorithm is diffraction limited. This is because, without knowledge of the illumination channels, the spatial cut-off frequency is solely determined by that of detection channels. The above shortcoming can be overcome by introducing a new image reconstruction algorithm combining the CTR-CLASS with methods that can reconstruct super-resolution images without prior knowledge of the illumination patterns, such as blind structured illumination microscopy31 and random illumination microscopy32,33. In this study, ballistic waves scattered once by an object are used for image reconstruction, and multiple-scattered waves inside a scattering medium are considered as background noise. However, multiple-scattered waves do also carry spatial information of the object. CTR-CLASS algorithm can potentially be extended to make the deterministic use of multiple-scattered waves in image reconstruction for further reducing measurement time or lowering the achievable spatial resolution well below the diffraction limit34.
For example, hundreds of engineers in the Design and Prototyping Group at the University of Sheffield Advanced Manufacturing Research Centre (AMRC) rely on open access to a fleet of 12 SLA 3D printers and a variety of engineering materials to support highly diverse research projects with industrial partners like Boeing, Rolls-Royce, BAE Systems, and Airbus. The team used High Temp Resin to 3D print washers, brackets, and a sensor mounting system that needed to withstand the elevated, and leveraged Durable Resin to create intricate custom springy components for a pick and place robot that automates composites manufacturing.
The most likely reason your video files aren't playing smoothly is because they are H.264 / AVC or H.265 / HEVC encoded files. DaVinci Resolve may be relying on your system CPU to decode these complex video files before handing over uncompressed image data to your GPU. Read more about this in my article XAVC / XAVC-S / H.264 / HEVC and DaVinci Resolve. It's likely that your CPU is the bottleneck if these video files are not playing back smoothly. The solution is to decrease the timeline resolution to HD if you are working with 4K video files, and to create optimized media or use render cache on your timeline.
Air Nozzles use the Coanda effect to amplify compressed airflow up to 25 times or more. Compressed air is ejected through a series of nozzles on the outer perimeter. As the air travels along the outer wall of the nozzle, surrounding air (blue arrows) is entrained into the stream. The airstream that results is a high volume, high velocity blast of air at minimal consumption. The air is always ejected so it can vent safely, well below OSHA dead end pressure requirements, should the nozzle end be blocked.
The inefficient use of compressed air for blowoff applications may create problems due to the energy costs, noise level and potential danger to personnel who are exposed to high pressure air. Open air pipes, copper tubes and drilled pipes are a few of the common abusers. They consume tremendous amounts of energy and often produce noise levels over 100 dBA.
The best way to cut energy costs is through proper maintenance and use of the compressed air system. Leaks and dirty filters require maintenance on a regular basis. Energy savings can also be realized when replacing outdated compressor motors and controls with high efficiency models that often pay for themselves in a short period of time.
The most important factor to dramatically boost efficiency is proper use. Using engineered products like EXAIR's Super Air Nozzles can cut operating costs since they use only a fraction of the compressed air of typical blowoffs. In addition, all of EXAIR's Air Nozzles and Jets can be cycled on and off with an instantaneous response. EXAIR's EFC is an electronic flow control that limits compressed air use by turning on the air only when a part is present.
Air can be dangerous when the outlet pressure of a hole, hose or copper tube is higher than 30 PSIG (2 BAR). In the event the opening is blocked by a hand or other body part, air may enter the bloodstream through the skin, resulting in a serious injury. All of the Air Nozzles and Jets manufactured by EXAIR have been designed for safety. All are safe to be supplied with higher pressure compressed air and meet OSHA standard 29 CFR 1910.242(b).
Consider the following example where a Model 1102 Mini Super Air Nozzle replaces a 1/8" open pipe. The compressed air savings is easy to calculate and proves to be dramatic. Payout for Air Nozzles and Jets, including filter and installation cost is measured in weeks - not years, as is the case for other cost reduction equipment. Based on a 40 hour work week, 52 weeks a year.
[3] M. Lustig, D. Donoho, and J. M. Pauly, ÒSparse MRI: The application of compressed sensing for rapid MR imaging.,Ó Magnetic resonance in medicine?: official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine, vol. 58, no. 6, pp. 1182-95, Dec. 2007 2ff7e9595c
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