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Imaging PET
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Course Layout Class + ContentDateClass Physical Principles of PET23.2.2005I Physical principles of MRI2.3.2005II Imaging applications9.3.2005III Image Reconstruction PET and MRI16.3.2005IV Automatic Image Alignment23.3.2005V PCA30.3.2005VI No Class6.4.2005VII GLM13.4.2005VIII GLM relation to classical tests (Anova, T-test..) 4.5.2005IX Covariates18.5.2005X Gaussian fields Theory25.5.2005XI Specific experiment design and analysis1.6.2005XII Specific experiment design and analysis8.6.2005XIII Correction for multiple measurements15.6.2005XIV
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Talk Layout Repetition of PET princinples Repetition of PET princinples PET image reconstruction -FBP PET image reconstruction -FBP Physics of NMR Physics of NMR Application to imaging of NMR -MRI Application to imaging of NMR -MRI
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PET
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Positron emission
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PET
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Coincidence Events 1 1. Detected True Coincidence Event 2 2. True Event Lost to Sensitivity or Deadtime 3 3. True Event Lost to Photon Attenuation 4 4. Scattered Coincidence Event 5a 5b 5a,b. Random Coincidence Event
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Attenuation Correction
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Filtered Back Projection
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Filtered backprojection Filter the measured projection data at different projection angles with a special function. Backproject the filtered projection data to form the reconstructed image. Filtering can be implemented in 2 ways, in the spatial domain, the filter operation is equivalent to to convolving the measured projection data using a special convolving function h(t) More efficient multiplication will be in the spatial frequency domain. FFT the measured projection data into the frequency domain: p(, )=FT {p(t, ) Multiply the the fourier transform projections with the special function. Inverse Fourier transform the product p ’ (, ).
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2D Vs. 3D
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Randoms
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Scatters
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Principles of MRI
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Felix Bloch
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Atoms
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Spins
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Precession
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RF pulse
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T1 and T2
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Effect of tissue T1 and T2 CONSTANTS T2 Constants at 1.5 T Controlled by TE T1 Constants at 1.5 T Controlled by TR 85Fat 45860Muscle 90780White matter 100920Gray matter 14003000CSF
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Slice selection
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K space
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K Space
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NMR
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