digital image processing

Digital Image Processing

Digital

Subtraction Angiography

and

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1

2

LUT Curve

Selection of Curve

Enhancing Visibility of Detail

Digital Subtraction Angiography

Digital Subtraction Angiography

DSA

Computed radiography

The need for subtraction

Subtraction for improvement in conspicuity

Mask image Live image Mask-Live(original) (original + contrast media)

Mask image Live image Live-Mask

Image processing with Java

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Subtraction methods1. Depth

2. Energy

3. Time

1. Temporal subtraction(Time-dependent)

Temporal subtraction

- 1. Pre contrast images (mask images)

- 2 . ( )Post contrast images live images

3 . Subtraction of mask from live images

2. Energy subtraction

- Energy dependence of x ray attenuation of difference tissue

Dual energy subtraction

Dual energy subtraction

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Advantage / Disadvantage

1. Provide selective cancellation

2. Fast , in millisecond, minimized motion interference

1. More complex

2. More sensitive to scatter radiation

3.Impossible to remove soft-tissue and bone simultaneously

Bone removed

- Soft tissue removed

Dual energy subtraction images

3. Hybrid subtraction

Temporal subtraction + Energ y subtraction

Image processing1. Spatial filtering

2. Pixel shifting operation

3. Temporal filtering

4. Intensity transformations

5. Window/Level techniques

6. Parametric imaging

1. Spatial filteringSpatial filtering is a method of selectively enhancing or dimi

nishing specific spatial frequency components in an image

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Digital filtering(Convo

lution)tttt ttttt tt ttt

pr ocessed i mages i s der i ved f r omt

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determined by the.

• MethodsLow-pass filteringHigh-pass filteringMedian filtering

Low-pass digital spatial filtering(Smoothing)

91

High-pass digital spatial filtering (Edge enhancement)

Filtered images

-Low passSmoothin

g

-High pass (Edge enhan

cement)

Original

Median filtering

Mask = Media n value of the

appropriate 9 pixels in the ori ginal image

Median filtering images

Digital chest radiog raph with unwanted

dot artifacts

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er to remove dots

2. Pixel shifting operation

• Rotation

• Translation

• Magnification

• Minification

Pixel registration to reduce moti on artifacts

3. Temporal filtering

1. Time interv al

difference(TID)

2 . Integratiot

3. Blurred mast tttttttt ttttttttttt

4. Recursive fittttttt (real

time methods)

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3.1. Time -interval difference subtraction

3.2. Integration

- -Pre contrast and post con trast images are summat

ed(integrated) to reducenoise

Image integration

Single pre-contrast image

Single post-contrast images

8 pre-contrast image

8 post-contrast image

3.3. Blurred mask temporal subtraction

For cardiac study : increase s/n for mask image and the

edge of cardiac will blurred

3.4. Recursive filtering (real time methods)

1. Reduce radiatio n dose 2. Reduce motion

artifacts

4. Intensity transformation

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Gamma correction curve

Gamma correction curves can be use to enhance or reduce contrast

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Histogram equalization

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e kidney

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Display

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Histogram equalization

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5. Windows / Level Techniques

1024

0

Window width W

Window center C

Gray scaledisplay

White

Black

Windowing

Double windows techniques

1024

0

Window 1

Gray scaledisplay

White

Black

WindowingWindow 2

6. Parametric imaging

• The algorithms for image processing that provide a final displayed image in which the value of each pixel is related to the attenuation or attenuation change at the particular point in the patient

Parametric(functional) imaging A cute T ubular

Necrosis

Example of parametric imaging1. Time to peak enhancement2. Mean transit time3. Maximum pixel attenuation4. Integrated attenuation change5. Local volume distribution

An idealized contrast enhancement curve tt ttttttttt tttttttt ttttt

6.Quantitative imaging : Temporal processing

Quantitative imaging Example of calculation

1. Peak or Maxi mumenhancement

2. Time to maximum enhancement

3. Time to half maximum enhancement

4. Integrated enhancement (areaundert he cur ve)

5. Mean transit time6. et c

ApplicationA. Cardiac outputB. Regional blood flowC. Cardiac ventricular ej

ection fractionD. Quantitation of left to

right shut E. etc

Gamma variate parameters of typical -time concent ration curve

A comparison between cardiac output estimations using D R and standard thermodilution methods

DSA quantitation of vessel stenosis

DSA of right coronary arte ry stenosis

Identifies the region of ste nosis, and normal portion,

then calculate the degree of narrowing

Boundary detection

1.After location of aortic valve pl

ane and apex , th e computer cons

tructs a ray pass ing through the

center(x) of theLV

2. A series of rays emanating from the center

are drawn by th e computer

3. The density of pixel values i

s measured , th e edge is deter

mined at 50% o f the maximum

values

-End diastolic ED contours

are shown for different thre

sholds values (5 0 % and

75%)

-End systolic ES contours ar

e shown for di fferent thresh

olds values(5 t0 7

5%)

The ejection fracti on is computed

using the 50% thr esholds silhouett

es

EDVESVEDV

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บรรณาน�กรม1. Image processing program with Java 2. Digital Subtraction Angiography.

USA,

http://rsb.info.nih.gov/ij/