Digital image processing
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and. Digital Image Processing. D igital S ubtraction A ngiography. วัตถุประสงค์. อธิบายขบวนการประมวลผลภาพดิจิตอลได้ อธิบายวิธีการปรับคอนทราสของภาพดิจิตอลได้ อธิบายการทำงานและควบคุม window ของภาพรังสีดิจิตอลได้ อธิบายวิธีการทำ Subtraction ภาพด้วยวิธีต่างๆ ได้. 1. 2. LUT Curve.

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Digital Image Processing

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Digital image processing

and

Digital Image Processing

Digital

Subtraction Angiography


Digital image processing

วัตถุประสงค์

  • อธิบายขบวนการประมวลผลภาพดิจิตอลได้

  • อธิบายวิธีการปรับคอนทราสของภาพดิจิตอลได้

  • อธิบายการทำงานและควบคุม window ของภาพรังสีดิจิตอลได้

  • อธิบายวิธีการทำ Subtraction ภาพด้วยวิธีต่างๆ ได้


Digital image processing

1

2


Digital image processing

LUT Curve


Digital image processing

Curve

Selection of


Digital image processing

Enhancing Visibility of Detail


D igital s ubtraction a ngiography

Digital Subtraction Angiography

DSA


Computed radiography

Computed radiography


The need for subtraction

The need for subtraction


Subtraction for improvement in conspicuity

Subtraction for improvement in conspicuity


Digital image processing

Mask image

Live image

Mask-Live

(original)

(original+ contrast media)


Digital image processing

Mask image

Live image

Live-Mask


Image processing with java

Image processing with Java

ให้นักศึกษาใช้ โปรแกรมนี้ในการทำ Digital Subtraction

ftp://rsbweb.nih.gov/pub/image-j/win32/


Subtraction methods

Subtraction methods

1. Depth

2. Energy

3. Time


Temporal subtraction time dependent

Temporal subtraction(Time-dependent)


Temporal subtraction

Temporal subtraction

1. Pre-contrast images (mask images)

2. Post-contrast images (live images)

3. Subtraction of mask from live images


2 energy subtraction

2. Energy subtraction

Energy dependence of x-ray attenuation of difference tissue


Dual energy subtraction

Dual energy subtraction


Dual energy subtraction1

Dual energy subtraction

Compton/Photoelectric decomposition


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

Advantage/ Disadvantage


Dual energy subtraction images

Dual energy subtraction images

Soft-tissue removed

Bone removed


3 hybrid subtraction

3. Hybrid subtraction

Temporal subtraction + Energy subtraction


Image processing

Image processing

1. Spatial filtering

2. Pixel shifting operation

3. Temporal filtering

4. Intensity transformations

5. Window/Level techniques

6. Parametric imaging


1 spatial filtering

Spatial filtering is a method of selectively enhancing or diminishing specific spatial frequency components in an image

1. Spatial filtering

Diagram of two-dimensional digital spatial filtering


Digital filtering convolution

Methods

Low-pass filtering

High-pass filtering

Median filtering

Digital filtering(Convolution)

Each pixel in the processed images is derived from a set of pixels in the original image as determined by the mask.


Low pass digital spatial filtering smoothing

Low-pass digital spatial filtering(Smoothing)


High pass digital spatial filtering edge enhancement

High-pass digital spatial filtering (Edge enhancement)


Filtered images

Filtered images

Original

High-pass

(Edge enhancement)

Low-pass

Smoothing


Medi an filtering

Median filtering

Mask = Median value of the appropriate 9 pixels in the original image


Median filtering images

Median filtering images

Digital chest radiograph with unwanted dot artifacts

After application of 3x1 medial filter to remove dots


2 pixel shifting operation

2. Pixel shifting operation

  • Rotation

  • Translation

  • Magnification

  • Minification


Digital image processing

Pixel registration to reduce motion artifacts


3 temporal filtering

3. Temporal filtering

1. Time interval difference(TID)

2. Integration

3. Blurred mask temporal subtraction

4. Recursive filtering (real time methods)

Generalized temporal filtering diagram


3 1 time interval difference subtraction

3.1. Time -interval difference subtraction


3 2 integration

3.2. Integration

Pre-contrast and post-contrast images are summated(integrated) to reduce noise


Image integration

Single pre-contrast image

Single post-contrast images

8 pre-contrast image

8 post-contrast image

Image integration


3 3 blurred mask temporal subtraction

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

3.4. Recursive filtering (real time methods)

1. Reduce radiation dose

2. Reduce motion artifacts


4 intensity transformation

4. Intensity transformation

Use of image processing to correct the non linearity of film


Gamma correction curve

Gamma correction curve

Gamma correction curves can be use to enhance or reduce contrast


Digital image processing

Contrast enhancement

Contrast reduction

Original image


Histogram equalization

Histogram equalization

Original arterial DSA image of the kidney

After histogram equalization


Histogram equalization1

Histogram equalization


5 windows level techniques

Gray scale

display

1024

White

Window

center C

Window

width W

Black

0

Windowing

5. Windows / Level Techniques


Double windows techniques

Gray scale

display

1024

White

Window 1

Black

Window 2

Windowing

0

Double windows techniques


6 parametric imaging

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

Parametric(functional) imaging

Acute Tubular Necrosis

Example of parametric imaging

1. Time to peak enhancement

2. Mean transit time

3. Maximum pixel attenuation

4. Integrated attenuation change

5. Local volume distribution


Digital image processing

6.Quantitative imaging : Temporal processing

An idealized contrast enhancement curve or Indicator dilution curve


Quantitative imaging

Example of calculation

1. Peak or Maximum enhancement

2. Time to maximum enhancement

3.Time to half maximum enhancement

4. Integrated enhancement(area under the curve)

5. Mean transit time

6. etc

Application

A. Cardiac output

B. Regional blood flow

C. Cardiac ventricular ejection fraction

D. Quantitation of left to right shut

E. etc

Quantitative imaging


Digital image processing

Gamma variate parameters of typical time-concentration curve


Digital image processing

A comparison between cardiac output estimations using DR and standard thermodilution methods


Dsa quantitation of vessel stenosis

DSA quantitation of vessel stenosis

Identifies the region of stenosis, and normal portion, then calculate the degree of narrowing

DSA of right coronary artery stenosis


Boundary detection

Boundary detection

1.After location of aortic valve plane and apex, the computer constructs a ray passing through the center(x) of the LV

2. A series of rays emanating from the center are drawn by the computer

3. The density of pixel values is measured , the edge is determined at 50% of the maximum values


Digital image processing

End-diastolicED contours are shown for different thresholds values(50% and 75%)

End-systolicES contours are shown for different thresholds values(50% and 75%)

The ejection fraction is computed using the 50% thresholds silhouettes


Digital image processing

แบบฝึกหัด

  • ให้ใช้ โปรแกรม ImageJ ซึ่งสามารถทำ Image processing ได้หลากหลายวิธี นำมาใช้เป็นเครื่องมือในการทำ subtraction โดยให้นักศึกษาเลือกภาพต้นฉบับของตนเอง(*.jpg)ขนาดไม่เกิน 500k ส่งให้อาจารย์ที่ web ของรายวิชา 437401 Medical imaging https://bme.kmitnb.ac.th/mmi1_elearning/ จากนั้นอาจารย์จะสร้างวัตถุแปลกปลอมในภาพนั้นและส่งกลับให้นักศึกษาเพื่อให้ นักศึกษาใช้โปรแกรม ในการสร้างภาพสิ่งแปลกปลอมนั้นและส่งกลับที่ web เดิม

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Digital image processing

บรรณานุกรม

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

  • Image processing program with Java

  • Digital Subtraction Angiography. USA,


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