Intensity correction of phased‐array surface coil images

Murakami, James W.; Hayes, Cecil E.; Weinberger, Ed

doi:10.1002/mrm.1910350419

Cited by 82 publications

(82 citation statements)

References 7 publications

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“…A number of approaches have been developed to correct the spatial nonuniformity of a coil's response including postprocessing methods (11)(12)(13)(14)(15)(16)(17) and RF field mapping approaches (18 -21). The sensitivity profile of a phased array coil generally can be removed through filtering, based on the assumption that the spatial nonuniformities vary smoothly.…”

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confidence: 99%

In vivo method for correcting transmit/receive nonuniformities with phased array coils

Wang

Qiu

Constable

2005

Magnetic Resonance in Med

102

111

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Phased array coils are finding widespread applications in both the research and the clinical setting. However, intensity nonuniformities with such coils can reduce the potential benefits of these coils, particularly for applications such as tissue segmentation. In this work, a method is described for correcting the nonuniform signal response based on in vivo measures of both the transmission field of body coil and the reception sensitivity of phased array coils, separately. For a uniform phantom, the reception sensitivity can be calculated using both Bloch equations and transmission field maps. For a heterogeneous object such as a brain, a minimal contrast acquisition must be obtained to map the receiver nonuniformities. This transmit field/ receiver sensitivity (TFRS) approach is compared with the standard methods of using the body coil to obtain a reference scan and low-pass filtering. The quantitative comparison results shows that the TFRS approach provides superior results in correcting intensity nonuniformities for a uniform phantom. This approach reduces the ratio between signal intensity SD of an image and its mean intensity from approximately 21% before correction to 13% after correction. Results are also shown demonstrating the utility of this approach in vivo with human brain images. The method is general and can be applied with most pulse sequences, any coil combination for transmission and reception, and in any anatomic region. Magn Reson Med 53:666 -674, 2005.

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confidence: 99%

In vivo method for correcting transmit/receive nonuniformities with phased array coils

Wang

Qiu

Constable

2005

Magnetic Resonance in Med

102

111

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“…6,7 We also assume that the high pixel values, especially in the cortical areas observed with scanner D, are caused by signal inhomogeneity from the uneven sensitivity of the multi-channel coil. 8,9 Although this method cannot fully compensate for machine-dependent issues, we believe that it can yield su‹cient results if the gradient polarity is the same and appropriate signal correction techniques are used, such as in scanners A and C.…”

Section: Discussionmentioning

confidence: 99%

Standardizing Display Conditions of Diffusion-weighted Images Using Concurrent b0 Images: A Multi-vendor Multi-institutional Study

et al. 2007

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Purpose: To establish a practical method that uses concurrent b0 images to standardize the display conditions for diŠusion-weighted images (DWI) that vary among institutions and interpreters.Method: Using identical parameters, we obtained DWI for 12 healthy volunteers at 4 institutions using 4 MRI scanners from 3 vendors. Three operators manually set the window width for the images equal to the signal intensity of the normal-appearing thalamus on b0 images and set the window level at half and then exported the images to 8-bit gray-scale images. We calculated the mean pixel values of the brain objects in the images and examined the variation among scanners, operators, and subjects.Result: Following our method, the DWI of the 12 subjects obtained using the 4 diŠerent scanners had nearly identical contrast and brightness. The mean pixel values of the brain on the exported images among the operators and subjects were not signiˆcantly diŠerent, but we found a slight, signiˆcant diŠerence among the scanners.Conclusion: Determining DWI display conditions by using b0 images is a simple and practical method to standardize window width and level for evaluating diŠusion abnormalities and decreasing variation among institutions and operators.

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“…Since measured image intensities obtained from a single coil element of the phased-array coil can be described as the product of the magnetization of the object being imaged and the surface coil's sensitivity profile (3), one can correct the intensity nonuniformity by dividing the surface-coil image by the estimated sensitivity profile of the coil.…”

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confidence: 99%

“…Various intensity-correction algorithms have been developed to estimate sensitivity profiles (2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14). These algorithms can be classified into two categories (15): prospective methods (2-9) and retrospective methods (10 -14).…”

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confidence: 99%

“…These estimates, however, do not take into account differences in coil loading when the imaged object is changed, and thus render an inaccurate representation of the sensitivity profile of the coil for the object to be imaged. Similarly, images of the object from a body coil can be used to estimate the sensitivity profile of phasedarray coil (3,8,9). However, all of these methods increase the imaging time for additional phantom/body coil imaging.…”

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Projection‐based estimation and nonuniformity correction of sensitivity profiles in phased‐array surface coils

Yun

Kyriakos

Chung

et al. 2007

Magnetic Resonance Imaging

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Purpose: To develop a novel approach for calculating the accurate sensitivity profiles of phased-array coils, resulting in correction of nonuniform intensity in parallel MRI. Materials and Methods:The proposed intensity-correction method estimates the accurate sensitivity profile of each channel of the phased-array coil. The sensitivity profile is estimated by fitting a nonlinear curve to every projection view through the imaged object. The nonlinear curve-fitting efficiently obtains the low-frequency sensitivity profile by eliminating the high-frequency image contents. Filtered back-projection (FBP) is then used to compute the estimates of the sensitivity profile of each channel. The method was applied to both phantom and brain images acquired from the phased-array coil.Results: Intensity-corrected images from the proposed method had more uniform intensity than those obtained by the commonly used sum-of-squares (SOS) approach. With the use of the proposed correction method, the intensity variation was reduced to 6.1% from 13.1% of the SOS. When the proposed approach was applied to the computation of the sensitivity maps during sensitivity encoding (SENSE) reconstruction, it outperformed the SOS approach in terms of the reconstructed image uniformity. Conclusion:The proposed method is more effective at correcting the intensity nonuniformity of phased-array surface-coil images than the conventional SOS method. In addition, the method was shown to be resilient to noise and was successfully applied for image reconstruction in parallel imaging.

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Intensity correction of phased‐array surface coil images

Cited by 82 publications

References 7 publications

In vivo method for correcting transmit/receive nonuniformities with phased array coils

In vivo method for correcting transmit/receive nonuniformities with phased array coils

Standardizing Display Conditions of Diffusion-weighted Images Using Concurrent b0 Images: A Multi-vendor Multi-institutional Study

Projection‐based estimation and nonuniformity correction of sensitivity profiles in phased‐array surface coils

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