‘U.’

U

AAPM

‘I

Tutorial

,v.

V

CT Image Perry

Sprawls,

Two

important

V

blur age

V

:

characteristics

of the

to visualize

and noise. detail);

jects.

Increased

increased ofblurring

in CT

by the

and

reduces

noise

be regulated

tomographic

structures

blurring visual

can

of the voxels,

computed

anatomic

Sources

(which

Noise1

PhD

the ability

affect

and

Detail

the

include

the

spot

the reconstruction

pathologic

the visibility

reduces focal

and

(CT)

size

size

filter

objects

sampling

the

selected.

are

(im-

of low-contrast

ofthe

and

that

features

of small

visibility

image

aperture

detector

Noise

ob-

size),

is caused

the

size

by the

variation in attenuation coefficients between voxels. Use of small voxels and edge-enhancing filters helps reduce blurring and improve visibility of fine details. However, small voxels absorb fewer photons and therefore result in increased noise. Noise can be reduced by using large voxels, increasing radiation dose, or using a smoothing filter, but this filter increases blurring. An optimized protocol for a specific clinical study must take these physical principles into account and be adjusted to give proper balance among detail, ;V

;

low noise,

and

patient

exposure.

INTRODUCTION Computed tomography (CT) is characterized makes it possible to depict the differences ever, CT has two other characteristics that structures

and

pathologic

of small

bility

objects

low-contrast This

features:

(image

by a high-contrast among

soft

affect

sensitivity

tissues

within

the ability

that

the

to visualize

body.

How-

anatomic

(a) blurring of the image, which affects the visiand (b) visual noise, which reduces visibility of

detail),

objects. article

shows

how

visibility

the sources ofblurring operator to optimize image

is influenced

by

these

two

characteristics,

identi-

and noise, and shows how they can be controlled quality for different clinical requirements.

fies

CHARACTERISTICS two characteristics that In CT, inherent contrast is the extent

by the

LESION Lesions

have

lesion

differs

that

differ

Index

terms:

from

1

From 1991

1992;

the

Department RSNA

6. Address ©RSNA,

from

Computed

RadioGraphics

the

that

greatly

of the

surrounding

of surrounding

(CT),

image

their

to which

those

tomography

visibility:

tissue.

quality

inherent

the attenuation tissue,

#{149} Computed

contrast

and

coefficient

value

If a lesion has attenuation it has high contrast and

tomography,

physics

#{149} Images,

quality

size.

of a

values will be

#{149} Physics

12: 1041-1046 ofRadiology,

scientific

reprint

affect

requests

assembly. to the

Emory Received

University May

28,

School 1992;

ofMedicine, revision

requested

1364 June

Clifton 9 and

Rd NE, Atlanta, received

July

GA 30322. 2; accepted

From July

author.

1992

1041

Figure

1.

matrix herent

Potential lesions are arranged in a according to their incontrast and size.

Figure

2.

(objects)

The

matrix

of po-

tential lesions shown in Figure 1 is depicted here with a curtain

of invisibility,

covers

the small

lesion

ner,

in the

which

low-contrast

upper

lesions.

Because

blurring ponents lesions

cor-

right

as well as many

other

of image

and noise (the cornofthis curtain), some in the body will not be

visible.

visualized. Generally, the easily

detail,

specifically

Physical size is also thought smaller the object, the greater

anatomic

detail.

Figure 1 illustrates how inherent contrast see lesions. The large, high-contrast lesion see. The challenge would be to detect the at the upper right. IMAGE

QUALITY

Each time an imaging procedure tential lesions that are not visible. lesions form

(Fig

in the body that of a contrast detail

of in terms of detail to be discerned. the capabilities must be for detecting and size interact and affect our ability in the lower left corner is very easy to lesion that is both small and low contrast

is conducted, there There is a distinct

to

is actually a large range of podividing line between those

are visible and those that are invisible. This boundary is one curve, which can be thought of as a “curtain of invisibility”

2).

We are generally concerned with image quality and improving image quality, which entails pushing the curtain of invisibility back so that more potential lesions or other objects are revealed. By changing certain imaging factors, we can raise the curtain and increase visibility. In doing this, however, we must be aware of other compromises in the imaging process. Two other specific characteristics of an image besides

contrast

oflow-contrast

anatomic

1042

U

RadioGrapbics

U

have objects,

detail

Sprawls

(Fig

an impact on visibility: (a) visual and (b) blurring, which affects 2).

noise, which affects visibility visibility of small objects and

Volume

12

Number

5

Focal Spot Size

Motion

I

III II

+

+

Sampling Aperture

Filter Smoothing

tI/-#{149}.. LII + LII I Ill

+

L1J.i Matrix

Detail

LI

-

V

I

Voxel Size

I Ill

Image

Figure

3.

(Blurring)

principles

imaging.

Aperture

pen,

fine

print,

noise

ing

procedures

from and

and

some

level

other

the

protocol

suffer

blurring.

In human

limits

our ability

which

Operators

of blurring

factors.

from

of blurring,

details.

amount

and

users

by selecting

In general,

as we

of CT can

appropriate

set up

the level of noise and the level lesions that will be visible.

As blurring

the

increases,

there

visibility

ofdetail

visibility

are specific

of the

sources

is limited

in

smaller

of image

by blurring

from

three

we

occasion-

to see small

vision,

objects,

control

the for

for a specific

objects

of imag-

clinical

proce-

We are affecting

is reduced. the

amount

various

In each

In conventional

sources:

As-

Md:

1987.)

of blurring.

blurring.

of medical

Rockville,

values

a protocol

dure, we are adjusting the range of potential

modality,

of detail

image.

physical

All image-forming

illusof blurring

FOV = field of view. (Reprinted, with permission, from Sprawls P. The a CT

FOV

Detector

ally suffer

Diagram

trates the sources that limit visibility

focal

imaging

Blurring

radiography, spot

size,

the

of receptor, and motion. Unlike radiography, which is affected during image acquisition, CT can be affected in the scanning stage reconstruction stage (Fig 3). During the scanning step of the image-forming process, blurring

by blurring and in the

the finite

size of the radia-

type

size of the focal

tion

detector,

tors.

For example, spot on one

focal

sectional

similar

(ie,

the

ray)

the object blurred.

in principle

of a ray,

from

both

is wider

but

also

than

the

In some CT scanners, would select the small user

can

select

(as in radiography) to the

and

blurring

is produced

by the finite

associated

with

radiographic

by recep-

a ray is the segment of an x-ray beam defined by the size of the end and by the size ofthe detector on the other end. The cross-

dimension

on the distance

spot

only image

and

often

referred

the focal the

object

surrounding

the user focal spot

change

the

to as the

spot

and

sampling

the detector.

being

imaged

tissue),

the

(ie,

image

If the the

ray

effective

size

of the

detector;

depends aperature

is “seeing”

ofthis

can choose the focal spot to give the greatest detail.

aperature, sampling

small

object

not

just

will

be

size and, obviously, In a few scanners, again,

for

the

maximum

detail, a relatively small detector aperture should be used. In the image reconstruction process, the section of tissue that was imaged is subdivided into individual tissue voxels, each ofwhich has a dimension. All structures within

ber. within achieve

September

an individual

In principle,

voxel

a voxel

are

mixed

together

is a three-dimensional

a voxel; when we look at images, we are an image with high detail, it is necessary

1992

and

represented

blur.

We cannot

seeing voxels to use small

by a single

CT num-

see any detail side by side. voxels.

To

Sprawls

U

RadioGrapbk.s

U

1043

FOV

(mm)

Voxel

+

Figure trates vidual

three

4. how voxel

factors:

Diagram illusthe size of an mdiis determined

by

field

of view size, and sec-

(FOV), matrix tion thickness. (Reprinted, with permission, from Sprawls P. The physical primciples of medical imaging. Rockville, Md: Aspen, 1987.)

5.

4

Matrix Size (voxels) (64, 128, 256, 512)

d=

L+

Matrix

Size

6.

Figures 5, 6. (5) CT scam with a moderate level of image noise demonstrates mires within the liver. (6) CT scan with a higher level of noise demonstrates duces the visibility of the vessels.

vascular

how

There are three protocol factors that can be adjusted that control voxel image detail: field ofview, matrix size, and section thickness (Fig 4). The mension of a voxel (sometimes erroneously referred to as the dimension

the ratio of the field ofview are imaging) to the matrix size (the pixel)

image). instances,

is

The

other dimension will be the largest

re-

size

and

face diof the

(the actual size of the anatomic region number of voxels across the dimension

of the voxel is the dimension. Section

struc-

noise

that we of the

section thickness, which, in most thickness is typically adjusted from

about 1 to 10 mm. The final factor that determines the amount of blurring produced in a CT image is the reconstruction filter. Reconstruction filters are mathematical operations that are used to alter characteristics of the image. In certain cases, it is desirable to use a socalled smoothing filter, which, in principle, is a blurring filter. In summary, the total blurring in an image that limits our ability to see the small features, potential lesions, or other anatomic structures has three basic sources. During scanning, the amount of blurring is determined by the sampling aperture (regulated primarily by focal spot size and detector size). At the time of reconstruction, blurring is determined by the size of the voxel and the type of filter. We need to recognize the characteristics ofblurring. Ifwe introduce a large amount of blurring at one point, there is no way to counteract it by decreasing the blurring at other points in the process. A chain is no stronger than its weakest link.

1044

U

RadioGraphics

U

Sprawls

Volume

12

Number

5

Figure

7. Diagram illushow noise results bethe same tissue can pro-

trates cause

duce

different

Note

that

CT numbers.

the

pixel

in the

right corner

lower than

the

Figure

other

8.

tamer

is brighter

one.

CT scan

ofwater

of a con-

in which

a cir-

cular area of interest is mdicated. Values for the mean .

.

VVVV

VVVVV.V:VV

(ME)

and

(SD)

ofthe

standard

deviation

CT numbers

are

shown.

L



:

V;

h.

t

/

;

r





; ;;





Visual noise affects visibility of low-contrast objects. In an image with low noise, we can see more low-contrast lesions. As the image noise increases, fewer and fewer low-contrast objects are visible (Figs 5, 6). Noise is caused by the variation in attenuation coefficients between individual

voxels.

In CT, we are measuring

the attenuation

coefficients

of the individual

Noise

tissue

voxels. Ifwe have two voxels ofidentical tissue, we would expect to measure identical attenuation coefficient values, and, when these are translated into CT numbers, we would expect to get similar numbers. In reality we do not. In Figure 7, two voxels of the same tissue produce different CT numbers. This is a statistical variation that is visualized as image noise. One way of evaluating noise is to produce a CT im-

age of a container of water. Water zero. However, a CT scan ofwater the

noise Noise

pixels

(Fig can

within

and

systems

and

quantified.

the

calculating

of interest

way

the

ofx-ray

photons

reduce

the

September

of of

and

do

a statistical

analysis

ofthe

number

of

the

of defining

amount

of noise a region

in CT

of interest

images.

All CT

and

measuring

deviation.

we must measure the attenuation coefficient A more precise measurement can be made

photons

CT number

and

capability

standard

in a voxel,

1992

count

of quantifying

software

To decrease noise, voxel more precisely. more

CT number because

the various CT numbers, the resultant statistiwould most likely be a bell-shaped curve. The amount of spread or be evaluated by determining the standard deviation, which is the easi-

excellent

have

number

Ifwe

a region

an

and has a defined in pixel brightness

8). be

cal distribution deviation can est

is homogeneous reveals variations

absorbed

in each

voxel

the more

precise

the measurement

error

that

appears

in the

during image

the

imaging

values for each by increasing the process.

will be, and

The

this will

as noise.

Sprawls

U

RadioGraphics

U

1045

Figure

9.

trates

how

reduced quantity sorbed

Diagram CT image

illusnoise

by increasing

the

photons abtissue voxel.

ofx-ray by each

This is determined posure size.

(MAS)

by the exand the voxel

The quantity ing

the

size

is

ofradiation

of the

photons

voxel

and

the

absorbed

exposure

can be controlled

(Fig

9).

Obviously,

in two ways: a large

voxel

will

cept and absorb more photons than a small voxel and will result in decreased in the image. The other way of controlling the quantity of absorbed radiation

adjustinter-

noise pho-

tons per voxel is by increasing the total radiation imparted to the patient. This is controlled through the milliampere seconds. By increasing the milliampere seconds, we deposit more photons in each voxel of tissue, which results in less statistical vanation, therefore less noise in the image.

The mathematical used

to control

teristics.

The

crease

noise

visibility

filters noise.

Many

smoothing

in the image

CT systems

filters

by using

of detail.

selected are

a smoothing

The

so-called

used

have

reconstruction

10 or i2 filters

to reduce

filter,

process

we

noise.

increase

edge-enhancing

or

the

with

can also be

different

Unfortunately,

blurring

characas we

and

detail-enhancing

de-

decrease filter

has

essen-

be selected when the primay goal is visualization of small detail. CT equipment manufacturers generally recommend which filters are useful for specific clinical procedures. Unfortunately, noise is a form of image detail. Anything we do to sharpen an image and increase detail, such as use of small voxels or edge-enhancing filters, will tially

also CONCLUSION

an

opposite

characteristic.

visibility

increase

A filter

of this

type

might

of noise.

We are concerned with the visibility ofobjects within the body, primarily lesions. As we consider lesions with respect to their size and inherent contrast, we have found that blurring of the image from several sources limits the visibility of the smaller objects and that visual noise limits visibility of the low-contrast objects. We can improve visibility of detail by using small voxels. However, when we use small voxels to push up the curtain of invisibility on the right and increase visibility of detail, the curtain will drop down on the left because those small voxels increase the noise (Fig 2). In controlling image quality, we must make compromises. An optimized protocol for a specific clinical study must take these physical principies into consideration and be adjusted to give a proper balance among detail (visibility of small posure.

SUGGESTED

READINGS

TH, Potts ofcomputed

Newton

pects

Mosby,

1046

U

RadioGraphics

U

objects),

1981.

Sprawls

low

DG, eds. tomography.

noise

(visibility

Technical

as-

St Louis:

oflow-contrast

objects),

and

patient

ex-

Sprawls P. The physical principles of medical imaging. Rockville, Md: Aspen,

1987.

Volume

12

Number

5

AAPM tutorial. CT image detail and noise.

Two important characteristics of the computed tomographic (CT) image that affect the ability to visualize anatomic structures and pathologic features ...
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