Imaging

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Imaging Imaging PET PET

description

Imaging. PET. Course Layout. Talk Layout. Repetition of PET princinples PET image reconstruction -FBP Physics of NMR Application to imaging of NMR -MRI. PET. Positron emission. PET. 5a. 5b. 4. 1. 2. 3. Coincidence Events. 1. Detected True Coincidence Event. - PowerPoint PPT Presentation

Transcript of Imaging

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ImagingImaging

PETPET

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Course LayoutCourse LayoutClassDateClass + Content

I23.2.2005Physical Principles of PET

II2.3.2005Physical principles of MRI

III9.3.2005Imaging applications

IV16.3.2005Image Reconstruction PET and MRI

V23.3.2005Automatic Image Alignment

VI30.3.2005PCA

VII6.4.2005No Class

VIII13.4.2005GLM

IX4.5.2005GLM relation to classical tests (Anova, T-test..)

X18.5.2005Covariates

XI25.5.2005Gaussian fields Theory

XII1.6.2005Specific experiment design and analysis

XIII8.6.2005Specific experiment design and analysis

XIV15.6.2005Correction for multiple measurements

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Talk LayoutTalk Layout Repetition of PET princinplesRepetition of PET princinples PET image reconstruction -FBPPET image reconstruction -FBP Physics of NMRPhysics of NMR Application to imaging of NMR -MRIApplication to imaging of NMR -MRI

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PETPET

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Positron emissionPositron emission

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PETPET

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Coincidence EventsCoincidence Events

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1. Detected True Coincidence Event

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2. True Event Lost to Sensitivity or Deadtime

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3. True Event Lost to Photon Attenuation

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4. Scattered Coincidence Event

5a 5b

5a,b. Random Coincidence Event

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Attenuation CorrectionAttenuation Correction

0 0

( ') ' ( ') ' ( ') '

1 2

x R R

x

x dx x dx x dx

p p p e e e

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Filtered Back ProjectionFiltered Back Projection

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FilteredFiltered B Baack Projectionck Projection

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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)

p t p t 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. 3D2D Vs. 3D

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RandomsRandoms

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ScattersScatters

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Principles of MRIPrinciples of MRI

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Felix BlochFelix Bloch

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AtomsAtoms

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SpinsSpins

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PrecessionPrecession

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RF pulseRF pulse

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T1 and T2T1 and T2

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T1 and T2T1 and T2

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T1 and T2T1 and T2

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Effect of tissueEffect of tissueT1 and T2 CONSTANTS

T1 Constants at 1.5 T Controlled by TR

T2 Constants at 1.5 T Controlled by TE

Fat85

Muscle86045

White matter78090

Gray matter920100

CSF30001400

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Slice selectionSlice selection

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K spaceK space

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K SpaceK Space

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NMRNMR