Retrospective correction of surface coil MR images using an automatic segmentation and modeling approach

Ross, Brian D.; Bland, Peyton H.; Meyer, Charles R.

doi:10.1002/(sici)1099-1492(199705)10:3<125::aid-nbm456>3.0.co;2-n

Cited by 5 publications

(1 citation statement)

References 16 publications

(14 reference statements)

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“…To correct the inhomogeneity of the surface coil MRI due to the modulation of coil reception sensitivity profiles, several approaches have been studied to estimate the coil profile, which is used to correct the measured inhomogeneous MRI [1][2][3][4][5][6][7][8][9][10][11][12]. These methods use either a theoretically generated model [1,3,13] of the coil or the information in the image itself [2,4,[6][7][8] to generate the expected coil sensitivity map.…”

Section: Introductionmentioning

confidence: 99%

Removing signal intensity inhomogeneity from surface coil MRI using discrete wavelet transform and wavelet packet

Lin¹,

Chen²,

Belliveau³

et al.

2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Abstract-We evaluate a combined discrete wavelet transform (DWT) and wavelet packet algorithm to improve the homogeneity of magnetic resonance imaging when a surface coil is used for reception. The proposed algorithm estimates the spatial sensitivity profile of the surface coil from the original anatomical image and uses this information to normalize the image intensity variations. Estimation of the coil sensitivity profile based on the wavelet transform of the original image data is found to provide a robust method for removing the slowly varying spatial sensitivity pattern.Keywords -MRI, wavelet packet, discrete wavelet transform, surface coil I. INTRODUCTIONSurface coils offer the potential for a 2 to 5 fold increase in sensitivity compared to volume coils. Despite of this signal-to-noise advantage, surface coils are not used regularly for many applications because of their small region of coverage and their intrinsically inhomogeneous reception profile. The limited coverage of a single small surface coil can be extended by using a phased array of multiple coils [1].The phased array technique also improves the homogeneity of the images in the plane of the array, but the image intensity is still significantly brighter near the coils than deeper in the brain. Thus, the surface coil detector has an inherently inhomogeneous reception profile that leads to a variation in intensity across the image. This significantly degrades the utility of the images for evaluation of pathology in the cortex.To correct the inhomogeneity of the surface coil MRI due to the modulation of coil reception sensitivity profiles, several approaches have been studied to estimate the coil profile, which is used to correct the measured inhomogeneous MRI [1][2][3][4][5][6][7][8][9][10][11][12]. These methods use either a theoretically generated model [1,3,13] of the coil or the information in the image itself [2,4,[6][7][8] to generate the expected coil sensitivity map. In the first case, knowledge of the location and orientation of each surface coil is required in addition to a B 1 field map generated from the coil geometry. In the second case, the coil intensity profile can be approximated by a low-pass filtered version of the original image. The low pass filter based approximation of the surface coil profile requires a priori knowledge of the anatomy and coil fall-off in order to determine the appropriate cut-off spatial frequency which separates the low frequency variations due to coil fall off from the higher spatial frequency variations due to the anatomy.Here we propose a solution to correcting surface coil image intensity variations using post-hoc processing of the original surface coil image. The method identifies edges in the image and uses this information to improve the estimation of the coil sensitivity map. The slowly varying intensity changes comprising the estimated coil sensitivity map are determined from a filter bank implementation. This method allows the comparison of multiple levels of spatial filtering. The optimum level...

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Section: Introductionmentioning

confidence: 99%

Removing signal intensity inhomogeneity from surface coil MRI using discrete wavelet transform and wavelet packet

Lin¹,

Chen²,

Belliveau³

et al.

2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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In Vivo Evidence for Cerebral Bioenergetic Abnormalities in Schizophrenia Measured Using³¹P Magnetization Transfer Spectroscopy

et al. 2014

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IMPORTANCE Abnormalities in neural activity and cerebral bioenergetics have been observed in schizophrenia (SZ). Further defining energy metabolism anomalies would provide crucial information about molecular mechanisms underlying SZ and may be valuable for developing novel treatment strategies. OBJECTIVE To investigate cerebral bioenergetics in SZ via measurement of creatine kinase activity using in vivo 31 P magnetization transfer spectroscopy. DESIGN, SETTING, AND PARTICIPANTS Cross-sectional case-control study in the setting of clinical services and a brain imaging center of an academic psychiatric hospital. Twenty-six participants with chronic SZ (including a subgroup diagnosed as having schizoaffective disorder) and 26 age-matched and sex-matched healthy control subjects (25 usable magnetic resonance spectroscopy data sets from the latter). INTERVENTION 31 P magnetization transfer spectroscopy. MAIN OUTCOMES AND MEASURES The primary outcome measure was the forward rate constant (k f) of the creatine kinase enzyme in the frontal lobe. We also collected independent measures of brain intracellular pH and steady-state metabolite ratios of high-energy phosphate-containing compounds (phosphocreatine and adenosine triphosphate [ATP]), inorganic phosphate, and the 2 membrane phospholipids phosphodiester and phosphomonoester. RESULTS A substantial (22%) and statistically significant (P = .003) reduction in creatine kinase k f was observed in SZ. In addition, intracellular pH was significantly reduced (7.00 in the SZ group vs 7.03 in the control group, P = .007) in this condition. The phosphocreatine to ATP ratio, inorganic phosphate to ATP ratio, and phosphomonoester to ATP ratio were not substantially altered in SZ, but a significant (P = .02) reduction was found in the phosphodiester to ATP ratio. The abnormalities were similar between SZ and schizoaffective disorder. CONCLUSIONS AND RELEVANCE Using a novel 31 P magnetization transfer magnetic resonance spectroscopy approach, we provide direct and compelling evidence for a specific bioenergetic abnormality in SZ. Reduced k f of the creatine kinase enzyme is consistent with an abnormality in storage and use of brain energy. The intracellular pH reduction suggests a relative increase in the contribution of glycolysis to ATP synthesis, providing convergent evidence for bioenergetic abnormalities in SZ. The similar phosphocreatine to ATP ratios in SZ and healthy controls suggest that the underlying bioenergetics abnormality is not associated with change in this metabolite ratio.

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A wavelet‐based approximation of surface coil sensitivity profiles for correction of image intensity inhomogeneity and parallel imaging reconstruction

Lin¹,

Chen²,

Belliveau³

et al. 2003

Human Brain Mapping

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We evaluate a wavelet-based algorithm to estimate the coil sensitivity modulation from surface coils. This information is used to improve the image homogeneity of magnetic resonance imaging when a surface coil is used for reception, and to increase image encoding speed by reconstructing images from under-sampled (aliased) acquisitions using parallel magnetic resonance imaging (MRI) methods for higher spatiotemporal image resolutions. The proposed algorithm estimates the spatial sensitivity profile of surface coils from the original anatomical images directly without using the body coil for additional reference scans or using coil position markers for electromagnetic model-based calculations. No prior knowledge about the anatomy is required for the application of the algorithm. The estimation of the coil sensitivity profile based on the wavelet transform of the original image data was found to provide a robust method for removing the slowly varying spatial sensitivity pattern of the surface coil image and recovering full FOV images from two-fold acceleration in 8-channel parallel MRI. The results, using bi-orthogonal Daubechies 97 wavelets and other members in this family, are evaluated for T1-weighted and T2-weighted brain imaging.

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Retrospective correction of surface coil MR images using an automatic segmentation and modeling approach

Cited by 5 publications

References 16 publications

Removing signal intensity inhomogeneity from surface coil MRI using discrete wavelet transform and wavelet packet

Removing signal intensity inhomogeneity from surface coil MRI using discrete wavelet transform and wavelet packet

In Vivo Evidence for Cerebral Bioenergetic Abnormalities in Schizophrenia Measured Using³¹P Magnetization Transfer Spectroscopy

A wavelet‐based approximation of surface coil sensitivity profiles for correction of image intensity inhomogeneity and parallel imaging reconstruction

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Retrospective correction of surface coil MR images using an automatic segmentation and modeling approach

Cited by 5 publications

References 16 publications

Removing signal intensity inhomogeneity from surface coil MRI using discrete wavelet transform and wavelet packet

Removing signal intensity inhomogeneity from surface coil MRI using discrete wavelet transform and wavelet packet

In Vivo Evidence for Cerebral Bioenergetic Abnormalities in Schizophrenia Measured Using31P Magnetization Transfer Spectroscopy

A wavelet‐based approximation of surface coil sensitivity profiles for correction of image intensity inhomogeneity and parallel imaging reconstruction

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In Vivo Evidence for Cerebral Bioenergetic Abnormalities in Schizophrenia Measured Using³¹P Magnetization Transfer Spectroscopy