Image Reconstruction Lecture 5

Front 1

algorithms
1)essential to the way computers process _______

Back 1

-information

Front 2

key points about algorithms (3)

Back 2

-all vagueness is eliminated
-rules are well defined
-terminate after a set of number of steps

Front 3

4 types of data

Back 3

-measurement data
-raw data
-convolution data
-image data

Front 4

fourier transformer
1)converts complex signals in _____ domain into a continuous spectrum of its sine & cosine components in the _______ domain

Back 4

-spatial
-frequency

Front 5

the coefficients of the ____ & _____ components make it possible to reconstruct an image in CT

Back 5

-sine
-cosine

Front 6

inverse fourier transformer reverts signal from the ____ domain back to ____ domain

Back 6

-frequency
-spatial

Front 7

measurement data is data ____ from the detectors

raw data
1)all data that is obtained from the detectors after it is ______
2)this is the data that is preserved & also called ______

Back 7

-direct
-preprocessed
-scan data

Front 8

convolution data is various mathematical convolution filters are applied to raw data to remove _____

Back 8

-blur

Front 9

convolution data has 2 parts

Back 9

-high & low pass convolution filters

Front 10

high pass convolution filters improve ______ by suppressing high spatial resolution (represented by bone- soft tissue interfaces)

low pass convolution filters improve ________ by suppressing low spatial frequencies (represented by a soft tissue like the brain & liver tissue

Back 10

-contrast resolution
-spatial resolution

Front 11

image data is known as _________ ______

Back 11

-reconstructed data

Front 12

pixel
1)____ that represents a small volume in the pt

voxel
1)is a volume element that has a _______ associated w it

Back 12

-2D
-linear attenuation coefficient

Front 13

the problem in CT is to reconstruct each _____ linear attenuation coefficient from many rays

Back 13

-voxel

Front 14

back projection is the simplest method
-___ all profiles to obtain an image
-causes _____ star patten _____

Back 14

-sums
-classical
-artifact

Front 15

step1 to reconstruction of algorithms
-collect the ____ sums from ____ degree angle & place them in the corresponding pixel elements

Back 15

-ray
-0

Front 16

step 2 to reconstruction of algorithms
-collect the ray sums from the ____ degree angle & add them to the corresponding pixel elements from step 1

Back 16

-45

Front 17

step 3 to reconstruction of algorithms
-collect ray sums from the _____ degree angle & add them to the corresponding pixel elements from step 2

Back 17

-90

Front 18

step 4 for reconstruction algorithms
-collect the ray sums from the ______ degree angle & add them to the corresponding pixel elements from step 3

Back 18

-135

Front 19

step 5 for reconstruction algorithms
-subtract a constant value ____

Back 19

-6

Front 20

step 6 for reconstruction algorithms
-____ by the common divisor ____ & you have the _____ matrix

Back 20

-reduce
-3
-original

Front 21

the fourier reconstruction method is used in _____ but not in ____ cause it requires more complicated math

Back 21

-MRI
-CT

Front 22

____ reconstruction was 1st reconstruction tech used by hounsfield in his brain studies

Back 22

-iterative

Front 23

________ is the most widely applied reconstruction algorithm in CT

Back 23

-filtered back projection