Physics: Mri (Image Formation)

Front 1

What is fourier transform

Back 1

The 1D Fourier transform is a mathematical procedure that allows a signal to be decomposed into its frequency components.

Front 2

What 3 parameters are needed to describe a sine wave with fourier transform

Back 2

amplitude
frequency
phase

Front 3

How is frequency determine

Back 3

Front 4

How is magnitude determined

Back 4

Front 5

What is the fourier transform

Back 5

The Fourier transform is a mathematical procedure that decomposes a signal into a sum of sine waves of different frequencies, phases and amplitude.

Front 6

By knowing frequency, amplitude and phase of each sine wave, is possible to reconstruct the signal (inverse Fourier transform).

Back 6

yes

Front 7

What tends to have a higher amplitude low or high frequency

Back 7

low frequency

Front 8

What is the right to left direction in MR

Back 8

X

Front 9

What is changing when moving from right to left

Back 9

the rows

Front 10

What type of frequency have the greatest change in intensity

Back 10

low spatial frequencies

Front 11

Do high spatial frequencies have low amplitude

Back 11

yes

Front 12

What describes the basic shape of the image

Back 12

low spatial frequencies

Front 13

What must be done to create a 2d image

Back 13

2D fourier transform

Front 14

How is a 2D fourier transform created

Back 14

first it is done in one direction(X ...right to left)

Front 15

What is the frequency domain

Back 15

Front 16

Is there a frequency domain in the X and Y direction

Back 16

yes

Front 17

Look and see how low spatial frequencies have the greatest change in intensity.

Back 17

Note that the big waves are low frequency and have the biggest change in intensity

Front 18

Note how the high spatial frequency have lower amplitudes

Back 18

small little waves (redline)

Front 19

What describes the general shape of an MR image

Back 19

General shape of the image is described by low spatial frequencies: this is also true with MRI images

Front 20

What is the 2nd step of the 2D fourier transform

Back 20

The second step of 2D Fourier transform is a second 1D Fourier transform in the orthogonal direction (column by column, Oy), performed on the result of the first one

Front 21

What is the image that can be created as a result of a fourier transform in the X and Y direction

Back 21

Front 22

What do the horizontal and vertical axis correspond to

Back 22

Horizontal and vertical axis correspond to horizontal and vertical spatial frequencies

Front 23

What determines the pixel intensity

Back 23

Pixel intensity corresponds to the amplitude (or magnitude) of frequency component

Front 24

What does the color correspond to

Back 24

Color corresponds to the phase of frequency component

Front 25

What are the 3 things encoded in a fourier plane

Back 25

Horizontal and vertical axis correspond to horizontal and vertical spatial frequencies
Pixel intensity corresponds to the amplitude (or magnitude) of frequency component
Color corresponds to the phase of frequency component.

Front 26

What is this called

Back 26

fourier plane

Front 27

What are the 3 components of a fourier plane

Back 27

Front 28

where is the MR signal stored

Back 28

The readout MR signal is stored in K-space which is equivalent to a Fourier plane.

Front 29

How do you go from a K-space to an image

Back 29

To go from a k-space data to an image requires using a 2D inverse Fourier Transform

Front 30

How do you go from a K-space to an image

Back 30

Front 31

What is required to go from K space to image formation

Back 31

To go from a k-space data to an image requires using a 2D inverse Fourier Transform.

Front 32

Are frequency-encoding and phase-encoding done so that data is spatially encoded by differences in frequency and phase, amenable to analysis by Fourier transform

Back 32

yes

Front 33

In k-space what is the horizontal spatial frequency replaced by

Back 33

Kx

Front 34

In K-space what is the vertical spacial frequency replaced by

Back 34

Ky coordinates

Front 35

What does the K-space coordinate system look like

Back 35

Front 36

Where does the K-space start to fill in following the 90° RF pulse + Slice-selection gradient :

Back 36

location at origin (center) of k-space

Front 37

Where does the K space fill if there is negative and strong phase encoding gradient

Back 37

moves to the lower bound of k-spac

Front 38

What line is filled in following a 180 RF pulse and the slice selection gradient

Back 38

moves to the opposite location

Front 39

Repetition for each line with increasing phase-encoding gradient strength (negative to positive intensity).

Back 39

The amount of gradient phase change between adjacent line is constant. This results in a sequential (line by line) filling of k-space from top to bottom.

Front 40

What determines the K space location in the Kx and Ky coordinate system

Back 40

The k-space location (kx and ky coordinates) of data is governed by the accumulated effect of gradient events and excitation pulses

Front 41

Where is the begining of the sequence in K space

Back 41

The initial RF excitation pulse (with the slice-selection gradient) is the beginning of the sequence: location is at the center of k-space.

Front 42

What governs the next movement in K-space

Back 42

the phase encoding gradient

Front 43

What determines what direction K space will go in the Y direction

Back 43

The greater the net strength of the phase-encoding gradient (or the longer the gradient is on), the farther from the k-space origin the data belong, in the upper direction if the gradient is positive or in the lower direction if the gradient is negative. As the duration of phase-encoding gradient is most often constant, the strength of the phase-encoding gradient governs the location on the vertical axis (ky-coordinate).

Front 44

What if there is a strong positive phase encoding gradient

Back 44

It will move up

Front 45

What happens if there is a negative phase encoding gradient

Back 45

it will move down

Front 46

What determines how far from the K space origin it will go

2

Back 46

The greater the net strength of the phase-encoding gradient (or the longer the gradient is on), the farther from the k-space origin the data belong,

Front 47

After the gradient moves up or down (Y-direction bc of phase encoding gradient), where does it go now

Back 47

right or left depending on the frequency encoding gradient

Front 48

If the phase encoding gradient was negative (previous example) and there is a strong positive frequency encoding gradient which direction doese K space fill

Back 48

to the right

Front 49

If the phase encoding gradient was negative (previous example) and there is a NEGATIVE frequency encoding gradient which direction doese K space fill

Back 49

to the left

Front 50

What determines the direction of K-space filling during the frequency encoding gradient

Back 50

The longer the frequency-encoding gradient is on (or the greater the net strength of the gradient is), the farther from the k-space origin the data belong, in the right direction if the gradient is positive or in the left direction if the gradient is negative. As the strength of the frequency-encoding gradient is most often constant, the duration of the frequency-encoding gradient governs the location on the horizontal axis (kx-coordinate)

Front 51

What happens following the 180 RF pulse

Back 51

if fills on the opposite side of K space

Front 52

What is the order of a standard spin echo sequence

Back 52

90 pulse
phase encoding
frequency encoding
180 degree pulse

Front 53

What is the order of filling in K space

Back 53

90 pulse -center
phase encoding - up or down
frequency encoding - L or R
180 pulse flip to other side

Front 54

How does phase encoding gradient strength dictate how the k-space is filled ing

Back 54

Repetition for each line with increasing phase-encoding gradient strength (negative to positive intensity). The amount of gradient phase change between adjacent line is constant. This results in a sequential (line by line) filling of k-space from top to bottom.