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2D FT Review MP/BME 574.

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Presentation on theme: "2D FT Review MP/BME 574."— Presentation transcript:

1 2D FT Review MP/BME 574

2 1D to 2D Sampling Signal under analysis is periodic
Signal is ‘essentially bandlimited’ Sampling rate is high enough to satisfy Nyquist criterion Other assumptions (for convenience) Signal is sampled with uniformly spaced intervals

3 2D Sampling/Discrete-Space Signal
1 n n2

4 2D Functions Impulses Step Sequences Separable Sequences
Periodic Sequences

5 Line Impulse 1 n n2

6 2D step n2 1 n

7 2D step 1 n n2

8 2D Step n2 1 n

9 Separable Sequences n2 1 n

10 Periodic Sequences 1 n n2

11 2D Convolution h(k1,k2) x(k1,k2) k1 k2 (3) (4) (1) (2) k2 k1

12 2D Convolution h(-k1,-k2) k1 k2 x(k1,k2) k2 (2) (1) (4) (3) k1

13 2D Convolution h(4-k1,3-k2) x(k1,k2) k1 k2 k2 (2) (1) (4) (3) 3-k2 k1

14 2D Convolution h(n1-k1,n2-k2) x(k1,k2) k1 k2 k2 (2) (1) (4) (3) (2)

15 2D Convolution h(n1-k1,n2-k2) y(n1,n2) k2 n2 (2) (1) (4) (3) (7) (7)
(6) (4) (6) n1 (2) k1 (1) (3) (3) n1-1

16 2D Convolution h(n1-k1,n2-k2) y(n1,n2) k2 n2 (2) (1) (4) (3) (7) (7)
(6) (10) (4) (6) n1 (2) k1 (1) (3) (3) n1-1

17 2DFT Imaging in MRI MP/BME 574

18 Abbe’s Theory of Image Formation
From Meyer-Arendt

19 No Magnetic Field = No Net Magnetization Random Orientation

20 Dipole Moments from Entire Sample
Magnetic Field (B0) Magnetic Field (B0) m m Positive Orientation Negative Orientation

21 Precession

22 Precession and Electromotive Force (emf) or Voltage
emf derives from Faraday’s law Time-dependent magnetic flux through a coil of wire Induces current flow Proportional to the magnetic field strength and the frequency of the field oscillation

23 Example x y z B1(t)

24 Example x y z B1(t)

25 Complex Voltage/Signal: General Case

26 rf-excitation By reciprocity, Lab Frame Rotating Frame
After Haacke, 1999

27 Quadrature Conversion in MRI (and Ultrasound) Signal Processing
Received Radio Frequency Echo Signal x(t) (fc = 10MHz; 40MS/s) X LPF xc(t) I—Channel 2 cos wct -p/2 Phase Shift -2 sin wct Q—Channel xs(t) X LPF In a high-end ultrasound/MR imaging system this conversion is done in the digital domain. In a lower-end system the conversion is done in the analog domain. Why?

28 Spatial Encoding

29 Slice Selection Ideal, non-selective rf: S(t) =rect(t/Dt) B1ideal(t)

30 Non-selective rf-pulse
Entire Volume Excited

31 FTdemo: Rect modulated Cosine

32 FTdemo: Rect modulated Cosine

33 Spatial Encoding Gradients
z B(r) r y x

34 Slice Selection Selective rf:
Ssel(t) = sinc(t/t) rect(t/Dt) B1ideal(t) Apply spatial gradient simultaneous to rf-pulse.

35 Slice Selective rf-pulse
Slice of width Dz Excited

36 FTdemo: Cosine modulated Sinc

37 Summary Spin ½ nuclei will precess in a magnetic field Bo
Excite and receive signal with coils (antennae) by Faraday’s Law Complex representation of real signals Quadrature detection Reciprocity Spatial magnetic field gradients Bandwidth of precessing “spins” Non-Selective rf pulses using Fourier transform principles Shift theorem etc… applies

38 Spatial Encoding Gradients
z B(r) r y x

39 Frequency Encoding f, B Df B=Bo xmin xmax FOVx

40 Frequency Encoding … … Recall Lab 2, Problem 4: Piano Keyboard
E, 660 Hz A, 220 Hz Middle C

41 Frequency Encoding Time (t) FT Temporal Frequency (f) Position (x)
Proportionality Temporal Frequency (f) Position (x)

42 Frequency Encoding

43 Frequency Encoding Spatial Frequency (k) Time (t) FT
Temporal Frequency (f) FT Proportionality Position (x) Spatial Frequency (k)

44 Phase Encoding y f, B Df B=Bo xmin xmax FOVx

45 Phase Encoding y f, B Df B=Bo xmin xmax FOVx

46 Phase Encoding y f, B Df B=Bo xmin xmax FOVx

47 Zero gradient for time, T
Phase Encoding y B Zero gradient for time, T y

48 Positive gradient for time, T
Phase Encoding y B Positive gradient for time, T y

49 Positive gradient for time, T
Phase Encoding y B Positive gradient for time, T y

50 Frequency Encoding Spatial Frequency (k-ko) Time (t) FT FT
Proportionality FT FT Proportionality Temporal Frequency (f) Position (x) e-igGyT

51 2D Fast GRE Imaging Gx Gy Gz RF TR = 6.6 msec TE Phase Encode
Dephasing/ Rewinder Asymmetric Readout Gy Dephasing/ Rewinder Gz Shinnar- LaRoux RF RF TR = 6.6 msec

52 2D FT y x k n Start Finish The elliptical centric view order is centric in both phase encode directions. Views are sampled based on their distance from the center of k-space. This leads to a radially symmetric distribution of contrast enhancement about the center of k-space.

53 3D Fast GRE Imaging Gx Gy Gz RF TR = 6.6 msec TE Phase Encode
Dephasing/ Rewinder Asymmetric Readout Gy Dephasing/ Rewinder Phase Encode Gz Shinnar- LaRoux RF RF TR = 6.6 msec

54 3D FT k z y x Tscan =Ny Nz TR NEX i.e. Time consuming! n
The elliptical centric view order is centric in both phase encode directions. Views are sampled based on their distance from the center of k-space. This leads to a radially symmetric distribution of contrast enhancement about the center of k-space.

55 Summary Frequency encoding Phase Entirely separable
Bandwidth of precessing frequencies Phase Incremental phase in image space Implies shift in k-space Entirely separable 1D column-wise FFT 1D row-wise FFT

56 Navigating in 2D k-Space
Goals Improve your intuition Specific examples Effects of: Apodization windowing “Zero-Padding” or Sinc interpolation Vendors refer to this as “ZIP” Sampling the corners of k-Space

57 Elliptical Centric View Order
k z High Detail Information k y Overall Image Contrast The elliptical centric view order is centric in both phase encode directions. Views are sampled based on their distance from the center of k-space. This leads to a radially symmetric distribution of contrast enhancement about the center of k-space. Sampled Points

58 MRI: Image Acquisition
FT FT K-space Image space

59 Case I Case II Case III ky kz

60 Case I k-space: Image Space: kz ky DFT
Bernstein MA, Fain SB, and Riederer SJ, JMRI 14: (2001)

61 Case II k-space: Image Space: kz ky FT

62 Case III k-space: Image Space: kz ky FT

63 a b

64 Zero-padding/Sinc Interpolation
Recall that the sampling theorem Restoration of a compactly supported (band-limited) function Equivalent to convolution of the sampled points with a sinc function

65 Recovering or “Restoring” f(x) from f(n):

66 Recovering or “restoring” f(x) from f(n):
Dx

67 Recovering or “Restoring” f(x) from f(n):

68 Recovering or “restoring” f(x) from f(n):
Dx

69 Recovering or “restoring” f(x) from f(n):
f(n’) where Dx

70 Case I k-space: Image Space: kz ky DFT
Bernstein MA, Fain SB, and Riederer SJ, JMRI 14: (2001)

71 Methods: Sampling Case I: Zero-filled k-space: Image Space: kz ky FT

72 Case II k-space: Image Space: kz ky FT

73 Case II k-space: Image Space: kz ky FT

74 Methods: Sampling Case III k-space: Image Space: kz ky FT

75 Methods: Sampling Case III: Zero-Filled k-space: Image Space: kz ky FT


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