Brainscape's Knowledge GenomeTM


Top Flashcards (Certified)
All Flashcards

CT Scan With Field Exposure > M Part I > Flashcards

M Part I Flashcards

1
Q

A precise step to be performed in a specific order to solve a problem
Basis for most computer programming

A

Algorithm

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

A mathematical method of creating missing data

A

Interpolation

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Two types of data

A

Raw data
Image data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

-have assigned value
-includes all measurements detailed from the detector array
-requires more storage space

A

Raw data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

The reconstruction that is automatically produced during scanning

A

Prospective Reconstruction

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

The process of generating new image after scanning

A

Retrospective Reconstruction

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Image data is also known as [..]

A

Reconstructed Data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Convolved data that have been back-projected into the image matrix to create CT images displayed on a monitor
Various digital filters are available to suppress noise and improved data

A

Image data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Factors that affect attenuation

A

Atomic no.
POI thickness
Energy of x-ray

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Those which result once the computer has processed the raw data
One HU is assigned to each pixel

A

Image Data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

IF ONLY IMAGE DATA IS AVAILABLE, DATA MANIPULATION IS [..]

A

LIMITED

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Reconstruction that can make slices thinner/thicker using raw data

A

Retrospective Reconstruction

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

The part of the beam that falls one irection

A

Ray

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

The detector senses each arriving ray and measures how much of the beam has been attenuated

A

Ray Sum

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

A complete set of ray sums

A

View

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

The system accounts for attenuation properties of each ray sum and correlates it to the position of the ray

A

Attenuation profile

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Reconstruction Algorithms (3)

A

Back Projection
Filtered Back Projection
Adaptive Statistical Iterative Reconstruction

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

Other names for Back Projecion

A

Summation Method/Linear Superposition Method

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

PROCESS of Back projection

A

Ray sum data acquired from each projection
Projected back onto the matrix

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

PROBLEM of Back Projection

A
  1. Low spatial resolution
  2. Bluming and produces star pattern artifact
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

Introduced to address the star pattern artifact

A

Filtered Back Projection

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

Process of applying a filter function to an attenuation profile

A

Convolution/Kernel Elements

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

Used in filtered back projection of reduce statistical noise

A

Fouler Theory

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

FILTER FUNCTIONS CAN ONLY BE APPLIED TO [..]

25
Starts with an assumption and compares this assumption with measured values, makes corrections to bring the two in agreement
Adaptive Statistical Iterative Reconstruction
26
Used in an iterative manner to extract additional image clarity and suppress noise
Statistical noise profiles
27
[adv] Adaptive Statistical Iterative Reconstruction
Improved image quality Reduced image noise
28
[importance] image display
Diff brightness- see pathologies in different configurations
29
Patients couch inserted then rotate (in-out)
Step and Shoot Scanning (1980s)
30
Continuous patient couch moving in while gantry rotates
Spiral/Helical CT Scanning
31
Used and defined as table distance travelled in one 360 deg rotation divided by beam collimation
Pitch
32
Refers to table movement (speed) in going in the gantry
Table feed per rotation
33
Pitch [formula]
Table feed per rotation/section width
34
[pitch] distance is enough Can adjust to rotation of X-ray tube
Pitch I
35
X-ray beam are contiguous for adjacent rotations
P = 1.0
36
X-ray beams are not contiguous for adjacent rotations [gaps in x-ray helix]
P>1.0
37
There is x-ray beam overlap
P<1.0
38
Getting data from same structure more than once
Oversampling
39
[disadv,adv] oversampling
Disadv: Increase pt dose Adv: Increase image quality due to increase SNR
40
Oversampling application
Facial bones Paranasal bones - frontal, sphenoidal, ethmoidal, maxillary
41
[adv,disadv] Of undersampling
Disadv. Lower pt does Adv. decreased image quality due to decreased SNR, more artifact
42
Undersampling application
Trauma CT angiography (contrast quickly flushed
43
Measure of the range of the CT number the image contains
Window Width (WW)
44
ALL VALUES HIGHER THAN SELECTED VALUES WILL APPEAR [..]
WHITE
45
ALL VALUES SELECTED LOWER THAN THE SELECTED VALUES WITHH APPEAR [..]
BLACK
46
Term for increasing window width
Widening the width
47
Selects which Hounsfield values are displayed as shades of gray (Center of WW) Roughly same value as tissue of interest
Window Level
48
Manipulation of the window width and level to optimize contrast
Windowing
49
COMPUTER CAN ASSIGN OVER [..] HU
2000
50
COMPUTER CAN DISPLAY [..] SHADES OF GRAY
256
51
NAKD EYE CAN ONLY DISTINGUISH ROUGHLY LESS THAN [..] SHADES OF GRY
40
52
Best used in areas of acute differing values [lungs, air and vessels is side by side]
Wide window width
53
excellent when examining areas of similar attenuation [soft tissue]
Narrow Window Width
54
WW UL AND LL FORMULA
UL = WL + (WW/2) LL = WL - (WW/2)
55
Helpful in reporting size of abnormality Essential for placement of biopsy needle or drainage apparatus
Distance Measurement
56
Used to make original image appear larger to see relevant data Clarify margins of abnormality
Image Magnification
57
Graphical display showing how frequently a range of CT no occurs within an area
Histogram
58
Allows more than one image to be displayed in a single frame
Multiple image display

CT Scan With Field Exposure (5 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2025 Bold Learning Solutions. Terms and Conditions