Image reconstruction in SNR units: A general method for SNR measurement
The method for phased array image reconstruction of uniform noise images may be used in conjunction with proper image scaling as a means of reconstructing images directly in SNR units. This facilitates accurate and precise SNR measurement on a per pixel basis. This method is applicable to root‐sum‐o...
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          | Published in | Magnetic resonance in medicine Vol. 54; no. 6; pp. 1439 - 1447 | 
|---|---|
| Main Authors | , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        Hoboken
          Wiley Subscription Services, Inc., A Wiley Company
    
        01.12.2005
     | 
| Subjects | |
| Online Access | Get full text | 
| ISSN | 0740-3194 1522-2594 1522-2594  | 
| DOI | 10.1002/mrm.20713 | 
Cover
| Abstract | The method for phased array image reconstruction of uniform noise images may be used in conjunction with proper image scaling as a means of reconstructing images directly in SNR units. This facilitates accurate and precise SNR measurement on a per pixel basis. This method is applicable to root‐sum‐of‐squares magnitude combining, B1‐weighted combining, and parallel imaging such as SENSE. A procedure for image reconstruction and scaling is presented, and the method for SNR measurement is validated with phantom data. Alternative methods that rely on noise only regions are not appropriate for parallel imaging where the noise level is highly variable across the field‐of‐view. The purpose of this article is to provide a nuts and bolts procedure for calculating scale factors used for reconstructing images directly in SNR units. The procedure includes scaling for noise equivalent bandwidth of digital receivers, FFTs and associated window functions (raw data filters), and array combining. Magn Reson Med, 2005. Published 2005 Wiley‐Liss, Inc. | 
    
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| AbstractList | The method for phased array image reconstruction of uniform noise images may be used in conjunction with proper image scaling as a means of reconstructing images directly in SNR units. This facilitates accurate and precise SNR measurement on a per pixel basis. This method is applicable to root-sum-of-squares magnitude combining, B(1)-weighted combining, and parallel imaging such as SENSE. A procedure for image reconstruction and scaling is presented, and the method for SNR measurement is validated with phantom data. Alternative methods that rely on noise only regions are not appropriate for parallel imaging where the noise level is highly variable across the field-of-view. The purpose of this article is to provide a nuts and bolts procedure for calculating scale factors used for reconstructing images directly in SNR units. The procedure includes scaling for noise equivalent bandwidth of digital receivers, FFTs and associated window functions (raw data filters), and array combining.The method for phased array image reconstruction of uniform noise images may be used in conjunction with proper image scaling as a means of reconstructing images directly in SNR units. This facilitates accurate and precise SNR measurement on a per pixel basis. This method is applicable to root-sum-of-squares magnitude combining, B(1)-weighted combining, and parallel imaging such as SENSE. A procedure for image reconstruction and scaling is presented, and the method for SNR measurement is validated with phantom data. Alternative methods that rely on noise only regions are not appropriate for parallel imaging where the noise level is highly variable across the field-of-view. The purpose of this article is to provide a nuts and bolts procedure for calculating scale factors used for reconstructing images directly in SNR units. The procedure includes scaling for noise equivalent bandwidth of digital receivers, FFTs and associated window functions (raw data filters), and array combining. The method for phased array image reconstruction of uniform noise images may be used in conjunction with proper image scaling as a means of reconstructing images directly in SNR units. This facilitates accurate and precise SNR measurement on a per pixel basis. This method is applicable to root-sum-of-squares magnitude combining, B1-weighted combining, and parallel imaging such as SENSE. A procedure for image reconstruction and scaling is presented, and the method for SNR measurement is validated with phantom data. Alternative methods that rely on noise only regions are not appropriate for parallel imaging where the noise level is highly variable across the field-of-view. The purpose of this article is to provide a nuts and bolts procedure for calculating scale factors used for reconstructing images directly in SNR units. The procedure includes scaling for noise equivalent bandwidth of digital receivers, FFTs and associated window functions (raw data filters), and array combining. The method for phased array image reconstruction of uniform noise images may be used in conjunction with proper image scaling as a means of reconstructing images directly in SNR units. This facilitates accurate and precise SNR measurement on a per pixel basis. This method is applicable to root‐sum‐of‐squares magnitude combining, B 1 ‐weighted combining, and parallel imaging such as SENSE. A procedure for image reconstruction and scaling is presented, and the method for SNR measurement is validated with phantom data. Alternative methods that rely on noise only regions are not appropriate for parallel imaging where the noise level is highly variable across the field‐of‐view. The purpose of this article is to provide a nuts and bolts procedure for calculating scale factors used for reconstructing images directly in SNR units. The procedure includes scaling for noise equivalent bandwidth of digital receivers, FFTs and associated window functions (raw data filters), and array combining. Magn Reson Med, 2005. Published 2005 Wiley‐Liss, Inc. The method for phased array image reconstruction of uniform noise images may be used in conjunction with proper image scaling as a means of reconstructing images directly in SNR units. This facilitates accurate and precise SNR measurement on a per pixel basis. This method is applicable to root‐sum‐of‐squares magnitude combining, B1‐weighted combining, and parallel imaging such as SENSE. A procedure for image reconstruction and scaling is presented, and the method for SNR measurement is validated with phantom data. Alternative methods that rely on noise only regions are not appropriate for parallel imaging where the noise level is highly variable across the field‐of‐view. The purpose of this article is to provide a nuts and bolts procedure for calculating scale factors used for reconstructing images directly in SNR units. The procedure includes scaling for noise equivalent bandwidth of digital receivers, FFTs and associated window functions (raw data filters), and array combining. Magn Reson Med, 2005. Published 2005 Wiley‐Liss, Inc. The method for phased array image reconstruction of uniform noise images may be used in conjunction with proper image scaling as a means of reconstructing images directly in SNR units. This facilitates accurate and precise SNR measurement on a per pixel basis. This method is applicable to root-sum-of-squares magnitude combining, B(1)-weighted combining, and parallel imaging such as SENSE. A procedure for image reconstruction and scaling is presented, and the method for SNR measurement is validated with phantom data. Alternative methods that rely on noise only regions are not appropriate for parallel imaging where the noise level is highly variable across the field-of-view. The purpose of this article is to provide a nuts and bolts procedure for calculating scale factors used for reconstructing images directly in SNR units. The procedure includes scaling for noise equivalent bandwidth of digital receivers, FFTs and associated window functions (raw data filters), and array combining.  | 
    
| Author | McVeigh, Elliot R. Kellman, Peter  | 
    
| Author_xml | – sequence: 1 givenname: Peter surname: Kellman fullname: Kellman, Peter email: kellman@nih.gov organization: Laboratory of Cardiac Energetics, National Heart, Lung and Blood Institute, National Institutes of Health, DHHS, Bethesda, Maryland 20892-1061, USA – sequence: 2 givenname: Elliot R. surname: McVeigh fullname: McVeigh, Elliot R. organization: Laboratory of Cardiac Energetics, National Heart, Lung and Blood Institute, National Institutes of Health, DHHS, Bethesda, Maryland 20892-1061, USA  | 
    
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/16261576$$D View this record in MEDLINE/PubMed | 
    
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| References | Noll DC, Nishimura DG, Macovski A. Homodyne detection in magnetic-resonance-imaging. IEEE Trans Med Imaging 1991; 10: 154-163. De Wilde JP, Lunt JA, Straughan K. Information in magnetic resonance images: evaluation of signal, noise and contrast. Med Biol Eng Comput 1997; 35: 259-265. Henkelman RM. Measurement of signal intensities in the presence of noise in MR images [Published erratum in Med Phys 1986;13:544]. Med Phys 1985; 12: 232-233. McKenzie CA, Yeh EN, Ohliger MA, Price MD, Sodickson DK. Self-calibrating parallel imaging with automatic coil sensitivity extraction. Magn Reson Med 2002; 47: 529-538. Pruessmann KP, Wieger M, Boernert P, Boesiger P. Advances in sensitivity encoding with arbitrary k-space trajectories. Magn Reson Med 2001; 46: 638-651. Constantinides CD, Atalar E, McVeigh ER. Signal-to-noise measurements in magnitude images from NMR phased arrays. [Published erratum in: Magn Reson Med. 2004 Jul;52:219]. Magn Reson Med 1997; 38: 852-857. Kellman P, Epstein FH, McVeigh ER. Adaptive sensitivity encoding incorporating temporal filtering (TSENSE). Magn Reson Med 2001; 45: 846-852. Walsh DO, Gmitro AF, Marcellin MW. Adaptive reconstruction of phased array MR imagery. Magn Reson Med 2000; 43: 682-690. Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P. SENSE: sensitivity encoding for fast MRI. Magn Reson Med 1999; 42: 952-962. Kellman P, Sorger JM, Epstein FH, McVeigh ER. Low-latency temporal filter design for real-time MRI using UNFOLD. Magn Reson Med 2000; 44: 933-939. de Zwart JA, van Gelderen P, Kellman P, Duyn JH. Application of sensitivity-encoded EPI for BOLD functional brain imaging. Magn Reson Med 2002 Dec; 48: 1011-1020. Roemer PB, Edelstein WA, Hayes CE, Souza SP, Mueller OM. The NMR phased array. Magn Reson Med 1990; 16: 192-225. Lai CM. Reconstructing NMR images under non-linear field gradients. J Phys E Sci Instrum 1983; 16: 34-38. Madore B, Glover GH, Pelc NJ. Unaliasing by Fourier encoding the overlaps using the temporal dimension (UNFOLD), applied to cardiac imaging and fMRI. Magn Reson Med 1999; 42: 813-828. Bendat JS, Piersol AG. Random Data: Analysis and Measurement Procedures. 3rd ed. New York: John Wiley & Sons; 2000. Sijbers J, Den Dekker AJ, Van Audekerke J, Verhoye M, Van Dyck D. Estimation of the noise in magnitude MR images. Magn Reson Imaging 1998; 16: 87-90. 1998; 16 2002; 47 2002; 48 2000 1990; 16 1991; 10 2000; 43 2000; 44 1997; 35 1997; 38 1999; 42 1985; 12 2001; 45 2001; 46 1983; 16 e_1_2_6_8_2 Bendat JS (e_1_2_6_7_2) 2000 e_1_2_6_9_2 e_1_2_6_4_2 e_1_2_6_3_2 e_1_2_6_6_2 e_1_2_6_5_2 e_1_2_6_12_2 e_1_2_6_13_2 e_1_2_6_2_2 e_1_2_6_10_2 e_1_2_6_11_2 e_1_2_6_16_2 e_1_2_6_17_2 e_1_2_6_14_2 e_1_2_6_15_2 Magn Reson Med. 2007 Jul;58(1):211-2  | 
    
| References_xml | – reference: Walsh DO, Gmitro AF, Marcellin MW. Adaptive reconstruction of phased array MR imagery. Magn Reson Med 2000; 43: 682-690. – reference: Roemer PB, Edelstein WA, Hayes CE, Souza SP, Mueller OM. The NMR phased array. Magn Reson Med 1990; 16: 192-225. – reference: Bendat JS, Piersol AG. Random Data: Analysis and Measurement Procedures. 3rd ed. New York: John Wiley & Sons; 2000. – reference: Constantinides CD, Atalar E, McVeigh ER. Signal-to-noise measurements in magnitude images from NMR phased arrays. [Published erratum in: Magn Reson Med. 2004 Jul;52:219]. Magn Reson Med 1997; 38: 852-857. – reference: De Wilde JP, Lunt JA, Straughan K. Information in magnetic resonance images: evaluation of signal, noise and contrast. Med Biol Eng Comput 1997; 35: 259-265. – reference: McKenzie CA, Yeh EN, Ohliger MA, Price MD, Sodickson DK. Self-calibrating parallel imaging with automatic coil sensitivity extraction. Magn Reson Med 2002; 47: 529-538. – reference: Noll DC, Nishimura DG, Macovski A. Homodyne detection in magnetic-resonance-imaging. IEEE Trans Med Imaging 1991; 10: 154-163. – reference: de Zwart JA, van Gelderen P, Kellman P, Duyn JH. Application of sensitivity-encoded EPI for BOLD functional brain imaging. Magn Reson Med 2002 Dec; 48: 1011-1020. – reference: Madore B, Glover GH, Pelc NJ. Unaliasing by Fourier encoding the overlaps using the temporal dimension (UNFOLD), applied to cardiac imaging and fMRI. Magn Reson Med 1999; 42: 813-828. – reference: Pruessmann KP, Wieger M, Boernert P, Boesiger P. Advances in sensitivity encoding with arbitrary k-space trajectories. Magn Reson Med 2001; 46: 638-651. – reference: Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P. SENSE: sensitivity encoding for fast MRI. Magn Reson Med 1999; 42: 952-962. – reference: Lai CM. Reconstructing NMR images under non-linear field gradients. J Phys E Sci Instrum 1983; 16: 34-38. – reference: Kellman P, Epstein FH, McVeigh ER. Adaptive sensitivity encoding incorporating temporal filtering (TSENSE). Magn Reson Med 2001; 45: 846-852. – reference: Kellman P, Sorger JM, Epstein FH, McVeigh ER. Low-latency temporal filter design for real-time MRI using UNFOLD. Magn Reson Med 2000; 44: 933-939. – reference: Henkelman RM. Measurement of signal intensities in the presence of noise in MR images [Published erratum in Med Phys 1986;13:544]. Med Phys 1985; 12: 232-233. – reference: Sijbers J, Den Dekker AJ, Van Audekerke J, Verhoye M, Van Dyck D. Estimation of the noise in magnitude MR images. Magn Reson Imaging 1998; 16: 87-90. – volume: 42 start-page: 952 year: 1999 end-page: 962 article-title: SENSE: sensitivity encoding for fast MRI publication-title: Magn Reson Med – volume: 46 start-page: 638 year: 2001 end-page: 651 article-title: Advances in sensitivity encoding with arbitrary k‐space trajectories publication-title: Magn Reson Med – volume: 48 start-page: 1011 year: 2002 end-page: 1020 article-title: Application of sensitivity‐encoded EPI for BOLD functional brain imaging publication-title: Magn Reson Med – volume: 16 start-page: 192 year: 1990 end-page: 225 article-title: The NMR phased array publication-title: Magn Reson Med – volume: 38 start-page: 852 year: 1997 end-page: 857 article-title: Signal‐to‐noise measurements in magnitude images from NMR phased arrays publication-title: Magn Reson Med – volume: 16 start-page: 34 year: 1983 end-page: 38 article-title: Reconstructing NMR images under non‐linear field gradients publication-title: J Phys E Sci Instrum – year: 2000 – volume: 35 start-page: 259 year: 1997 end-page: 265 article-title: Information in magnetic resonance images: evaluation of signal, noise and contrast publication-title: Med Biol Eng Comput – volume: 12 start-page: 232 year: 1985 end-page: 233 article-title: Measurement of signal intensities in the presence of noise in MR images publication-title: Med Phys – volume: 10 start-page: 154 year: 1991 end-page: 163 article-title: Homodyne detection in magnetic‐resonance‐imaging publication-title: IEEE Trans Med Imaging – volume: 43 start-page: 682 year: 2000 end-page: 690 article-title: Adaptive reconstruction of phased array MR imagery publication-title: Magn Reson Med – volume: 16 start-page: 87 year: 1998 end-page: 90 article-title: Estimation of the noise in magnitude MR images publication-title: Magn Reson Imaging – volume: 47 start-page: 529 year: 2002 end-page: 538 article-title: Self‐calibrating parallel imaging with automatic coil sensitivity extraction publication-title: Magn Reson Med – volume: 42 start-page: 813 year: 1999 end-page: 828 article-title: Unaliasing by Fourier encoding the overlaps using the temporal dimension (UNFOLD), applied to cardiac imaging and fMRI publication-title: Magn Reson Med – volume: 45 start-page: 846 year: 2001 end-page: 852 article-title: Adaptive sensitivity encoding incorporating temporal filtering (TSENSE) publication-title: Magn Reson Med – volume: 44 start-page: 933 year: 2000 end-page: 939 article-title: Low‐latency temporal filter design for real‐time MRI using UNFOLD publication-title: Magn Reson Med – ident: e_1_2_6_4_2 doi: 10.1016/S0730-725X(97)00199-9 – ident: e_1_2_6_13_2 doi: 10.1109/42.79473 – ident: e_1_2_6_12_2 doi: 10.1002/mrm.1241 – ident: e_1_2_6_15_2 doi: 10.1002/1522-2594(200012)44:6<933::AID-MRM15>3.0.CO;2-I – ident: e_1_2_6_3_2 doi: 10.1002/mrm.1910380524 – ident: e_1_2_6_14_2 doi: 10.1002/(SICI)1522-2594(199911)42:5<813::AID-MRM1>3.0.CO;2-S – ident: e_1_2_6_2_2 doi: 10.1118/1.595711 – ident: e_1_2_6_8_2 doi: 10.1002/mrm.1910160203 – volume-title: Random Data: Analysis and Measurement Procedures year: 2000 ident: e_1_2_6_7_2 – ident: e_1_2_6_5_2 doi: 10.1007/BF02530047 – ident: e_1_2_6_17_2 doi: 10.1002/mrm.10303 – ident: e_1_2_6_10_2 doi: 10.1002/(SICI)1522-2594(200005)43:5<682::AID-MRM10>3.0.CO;2-G – ident: e_1_2_6_11_2 doi: 10.1002/mrm.1113 – ident: e_1_2_6_16_2 doi: 10.1088/0022-3735/16/1/007 – ident: e_1_2_6_9_2 doi: 10.1002/mrm.10087 – ident: e_1_2_6_6_2 doi: 10.1002/(SICI)1522-2594(199911)42:5<952::AID-MRM16>3.0.CO;2-S – reference: - Magn Reson Med. 2007 Jul;58(1):211-2  | 
    
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| SubjectTerms | Algorithms Computer Simulation Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Information Storage and Retrieval - methods Magnetic Resonance Imaging - instrumentation Magnetic Resonance Imaging - methods Models, Biological Models, Statistical MRI noise parallel MRI Phantoms, Imaging phased array Reproducibility of Results SENSE Sensitivity and Specificity Signal Processing, Computer-Assisted SNR measurement Stochastic Processes  | 
    
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| Title | Image reconstruction in SNR units: A general method for SNR measurement | 
    
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