A Review on Potential Issues and Challenges in MR Imaging

Srinivasan, Kathiravan; Kanakaraj, J.

doi:10.1155/2013/783715

Cited by 24 publications

(17 citation statements)

References 15 publications

(16 reference statements)

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“…Abbreviations used: 2D/3D, two−/three-dimensional; FoV, field of view; MRI, magnetic resonance imaging; RF, radiofrequency; ROI, region of interest; SNR, signalto-noise ratio Birdcage coils provide uniform excitation (B 1 + ) and reception (B 1 − ) magnetic fields within their internal volume. 7 The areas of field homogeneity provided by such coils are sufficient for small-animal, whole-body imaging, even at high frequencies, where the wavelength of the radiofrequency (RF) field used shortens, leading to uniformity issues in human MRI. 8 The downside of the use of volume coils is the low sensitivity that they provide and the large area from which they collect noise.…”

Section: Introductionmentioning

confidence: 99%

Small‐animal, whole‐body imaging with metamaterial‐inspired RF coil

et al. 2018

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Particular applications in preclinical magnetic resonance imaging require the entire body of an animal to be imaged with sufficient quality. This is usually performed by combining regions scanned with small coils with high sensitivity or long scans using large coils with low sensitivity. Here, a metamaterial-inspired design employing a parallel array of wires operating on the principle of eigenmode hybridization was used to produce a small-animal imaging coil. The coil field distribution responsible for the coil field of view and sensitivity was simulated in an electromagnetic simulation package and the coil geometrical parameters were optimized for whole-body imaging. A prototype coil was then manufactured and assembled using brass telescopic tubes with copper plates as distributed capacitance. Its field distribution was measured experimentally using the B mapping technique and was found to be in close correspondence with the simulated results. The coil field distribution was found to be suitable for large field of view small-animal imaging and the coil image quality was compared with a commercially available coil by whole-body scanning of living mice. Signal-to-noise measurements in living mice showed higher values than those of a commercially available coil with large receptive fields, and rivalled the performance of small receptive field and high-sensitivity coils. The coil was deemed to be suitable for some whole-body, small-animal preclinical applications.

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Section: Introductionmentioning

confidence: 99%

Small‐animal, whole‐body imaging with metamaterial‐inspired RF coil

et al. 2018

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“…This is most often a superconducting electromagnet but it could also be a permanent magnet. Added to this is a coil to generate the radiofrequency electromagnetic field (the “RF field”) and, lastly, there are the imaging gradient coils, responsible for creating the spatial‐encoding magnetic fields and typically referred to as “the gradients.” While essential in allowing the MRI device to produce images, these coils and the manner in which the fields they generate interact with matter can also, at times, be the cause of serious threats to human life and limb …”

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confidence: 99%

“…While essential in allowing the MRI device to produce images, these coils and the manner in which the fields they generate interact with matter can also, at times, be the cause of serious threats to human life and limb. [1][2][3][4][5][6][7][8][9][10] This article explores the physics underlying the safety risks associated with the three principal types of coils and magnets. A number of other reviews and expos es exist that cover the basic physics behind the interactions of one or more of these and are recommended as supplemental reading.…”

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confidence: 99%

The physics of MRI safety

Panych

Madore

2017

Magnetic Resonance Imaging

133

155

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The main risks associated with magnetic resonance imaging (MRI) have been extensively reported and studied; for example, everyday objects may turn into projectiles, energy deposition can cause burns, varying fields can induce nerve stimulation, and loud noises can lead to auditory loss. The present review article is geared toward providing intuition about the physical mechanisms that give rise to these risks. On the one hand, excellent literature already exists on the practical aspect of risk management, with clinical workflow and recommendations. On the other hand, excellent technical articles also exist that explain these risks from basic principles of electromagnetism. We felt that an underserved niche might be found between the two, ie, somewhere between basic science and practical advice, to help develop intuition about electromagnetism that might prove of practical value when working around MR scanners. Following a wide‐ranging introduction, risks originating from the main magnetic field, the excitation RF electromagnetic field, and switching of the imaging gradients will be presented in turn. Level of Evidence: 5 Technical Efficacy: 1 J. Magn. Reson. Imaging 2018;47:28–43.

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“…Also, it can be witnessed that the false-positive ratio gets minimized to 18 percent.Electronics 2020, 9, 45 2 of 13 be observed that enabling technologies for smart tire quality assessment for realizing intelligent tire manufacturing has been gaining prominence to address challenges such as automated tire defects detection.Generally, it can be witnessed that in the modern-day scenario, there is a humongous and swift growth in the gadgets, equipment, and devices connected to the internet. These devices, gadgets, and equipment have profound computing characteristics, and at the same time, they are exceedingly performance-oriented [2]. Due to all these facts, the concept of deep learning has evolved into a newer dimension, and it plays a significant part in processing and recognizing images, speech, and video, and so on.…”

mentioning

confidence: 99%

“…Generally, it can be witnessed that in the modern-day scenario, there is a humongous and swift growth in the gadgets, equipment, and devices connected to the internet. These devices, gadgets, and equipment have profound computing characteristics, and at the same time, they are exceedingly performance-oriented [2]. Due to all these facts, the concept of deep learning has evolved into a newer dimension, and it plays a significant part in processing and recognizing images, speech, and video, and so on.…”

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confidence: 99%

Quality Assessment of Tire Shearography Images via Ensemble Hybrid Faster Region-Based ConvNets

et al. 2019

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In recent times, the application of enabling technologies such as digital shearography combined with deep learning approaches in the smart quality assessment of tires, which leads to intelligent tire manufacturing practices with automated defects detection. Digital shearography is a prominent approach that can be employed for identifying the defects in tires, usually not visible to human eyes. In this research, the bubble defects in tire shearography images are detected using a unique ensemble hybrid amalgamation of the convolutional neural networks/ConvNets with high-performance Faster Region-based convolutional neural networks. It can be noticed that the routine of region-proposal generation along with object detection is accomplished using the ConvNets. Primarily, the sliding window based ConvNets are utilized in the proposed model for dividing the input shearography images into regions, in order to identify the bubble defects. Subsequently, this is followed by implementing the Faster Region-based ConvNets for identifying the bubble defects in the tire shearography images and further, it also helps to minimize the false-positive ratio (sometimes referred to as the false alarm ratio). Moreover, it is evident from the experimental results that the proposed hybrid model offers a cent percent detection of bubble defects in the tire shearography images. Also, it can be witnessed that the false-positive ratio gets minimized to 18 percent.Electronics 2020, 9, 45 2 of 13 be observed that enabling technologies for smart tire quality assessment for realizing intelligent tire manufacturing has been gaining prominence to address challenges such as automated tire defects detection.Generally, it can be witnessed that in the modern-day scenario, there is a humongous and swift growth in the gadgets, equipment, and devices connected to the internet. These devices, gadgets, and equipment have profound computing characteristics, and at the same time, they are exceedingly performance-oriented [2]. Due to all these facts, the concept of deep learning has evolved into a newer dimension, and it plays a significant part in processing and recognizing images, speech, and video, and so on. Furthermore, the implementation of a deep learning paradigm for automation in conventional manufacturing units significantly minimizes the usage of physical labor, and it also enhances the overall competence and efficacy of these units. Digital shearography is a laser-based measuring approach that relies on the processing of digital data, interferometry, and phase-shifting paradigm [3-5].A shearography system was developed by applying a spatial light modulator for controlling the amount of shearing and the direction of the phase light automatically and accurately. The system eliminates the nonlinear random error and enhances the efficiency of testing [6]. A system was developed using shearography to examine the exterior heatproof covering of a cylinder, and defect detection was done using an artificial intelligence-based recognition algorithm for deep...

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A Review on Potential Issues and Challenges in MR Imaging

Cited by 24 publications

References 15 publications

Small‐animal, whole‐body imaging with metamaterial‐inspired RF coil

Small‐animal, whole‐body imaging with metamaterial‐inspired RF coil

The physics of MRI safety

Quality Assessment of Tire Shearography Images via Ensemble Hybrid Faster Region-Based ConvNets

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