Ct Module 5: Image Reconstruction

Front 1

algorithm

Back 1

set of rules or directions for getting a specific output from a specific input

Front 2

convolution

Back 2

digital image processing technique to modify images through a filter function

Front 3

interpolation

Back 3

a mathematical technique to estimate the value of a function from known values on either side of the function

Front 4

Fourier Transform

Back 4

mathematical transformation to transform spatial domain to frequency domain

Front 5

Sequence of events after signals leave the detectors

Back 5

ct detectors -> preprocessing -> reformatted raw data -> convolution with filters -> image reconstruction algorithm (back projection) -> reconstructed images of CT numbers -> image storage, display, recording, archiving.

Front 6

image reconstruction from projections

Back 6

reconstruction of images from different planes.

Front 7

3 notable ct people

Back 7

oldendorf (1961)

cormack (1963, 1964)

hounsfield (1971)

Front 8

oldendorf (1961)

Back 8

prototype ct scanner

Front 9

hounsfield (1971)

Back 9

prototype scanner using Americium Gamma Radiation Source.

a homogeneous beam of radiation

used parallel beam projection acquired through 180 degree rotation.

Front 10

cormack (1963-1964)

Back 10

cormack's scanner

Front 11

identify three classes of reconstruction algorithms.

Back 11

1. back projection algorithm
2. iterative algorithm
3. analytic algorithms

Front 12

back projection

Back 12

Back-projection results in an unsharp image. star pattern.
-summation method/linear superposition method

Front 13

filtered back projection

Back 13

Filtered back-projection uses a digital filter (a convolution filter) to remove this blurring, which produces a sharp image.

Front 14

state the role of interpolation in image reconstruction in single- and multi-slice CT

Back 14

to estimate the value of a function from known values on either side of the function.

Front 15

list four operations of a 3D surface display technique

Back 15

-interpolation
-segmentation
-surface formation
-projection

Front 16

ray sum

Back 16

number of xrays attenuated at a detector.

Front 17

iterative algorithms

Back 17

starts with an assumption, compares assumption with measure values, makes corrections to bring the two into agreement, repeat until agree or within acceptable limits

Front 18

limitations of iterative algorithms

Back 18

-difficult to obtain accurate ray sums due to quantum noise and pt. motion.

-takes too long to generate reconstructed image

Front 19

does fourier reconstruction use any filtering? why or why not?

Back 19

no, interpolation does the same thing.