Digital image processing
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Digital Image Processing. Thanks to the work of Dr. Perry Sprawls of Emory University and the Sprawls Educational Foundation, this material is available on-line. Digital Image Processing.

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Digital Image Processing

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Digital image processing

Digital Image Processing

Thanks to the work of Dr. Perry Sprawls of Emory University and the Sprawls Educational Foundation, this material is available on-line.


Digital image processing1

Digital Image Processing

  • A major advantage of having images in digital format is the ability to perform a variety of image processing procedures with a computer.

  • The procedures are selected and adjusted to change the characteristics of the images.


Digital image processing2

Digital Image Processing

  • Processing purposes:

  • Improve quality

  • Optimize characteristics for maximum visibility


Changing image characteristics

Changing Image Characteristics

  • Processing can change most image properties.

  • Three possibilities include:

    • Reduce Image Noise

    • Increase Detail

    • Adjust and Optimize image contrast


Contrast adjustment with processing

Contrast Adjustment with Processing

  • While there are many processes that can be used to adjust contrast, the most common ones are:

  • Look Up Table (LUT) processing

  • Windowing

  • Both are used in DR and other imaging modalities.


Using digital processing to change image contrast

Using Digital Processing to Change Image Contrast

  • Here is a very simple image to show how digital processing can be used to change contrast.

  • The image consists of a background area with a small square in the middle.


Using digital processing to change image contrast1

Using Digital Processing to Change Image Contrast

  • The background has a value of 40 and the small square a value of 30.

  • The numerical contrast would be 10 (40-30=10).

  • A numerical value of 10 would be low contrast.


Using digital processing to change image contrast2

Using Digital Processing to Change Image Contrast

  • Look up tables are data stored in the computer that is used to substitute new values for each pixel.

  • In this simple example we have values of only 30 and 40.


Using digital processing to change image contrast3

Using Digital Processing to Change Image Contrast

  • As we see here, the processing uses a LUT that substitutes 90 for 40 and 10 for 30.

  • The effect is to increase image contrast.

  • 90-10=80 or improved contrast.


Using digital processing to change image contrast4

Using Digital Processing to Change Image Contrast

  • As we will discover, it is usually possible for the user to select from a variety of LUTs, each one designed to produce specific contrast characteristics.


Lut described by graphs

LUT described by Graphs

  • Lets recall that a LUT indicates what number is substituted for each pixel value during image processing.

  • It is very helpful to show this relationship between the original pixel value and the new pixel values.


Lut described by graphs1

LUT described by Graphs

  • This is a simple straight line or linear graph that show the same values for the original and processed value.

  • Processing with this LUT does not change the image, it just introduces us to the concept of LUTs.


Lut curve

LUT Curve

  • If LUT processing is to change the contrast characteristics, it must substitute numbers that are different from the original pixel values.


Lut curve1

LUT Curve

  • You should recognize this curve as being similar to that of a radiographic film H & D curve.

  • That is intentional.

  • By processing a digital image with this characteristic it takes on some of the familiar contrast “look” of an image recorded on film.


Selection of luts

Selection of LUTs

  • One of the advantages of digital processing is that the processing parameters (factors) can be selected to produce images with different contrast characteristics.

  • Here we have three different LUTs.


Selection of luts1

Selection of LUTs

  • Like the characteristic curve of film, the slope of the curve at every point represents how the contrast will be changed by processing.

  • If the slope is greater than 45º the contrast will be increased.


Selection of luts2

Selection of LUTs

  • If the slope is less than 45º, the contrast will be reduced by processing.

  • The curve with greater slope will produce higher contrast.

  • The one with less slope will produce more latitude or more like wide latitude type film used in chest radiography. We will look at inverted later.


Lut selection

LUT Selection

  • In the typical digital radiography system, a variety of LUTs are installed.

  • The appropriate LUT is then automatically selected to give the desired contrast characteristics for that procedure (chest, extremity, spine, etc) that is designated by the operator.


Processing to increase image contrast

Processing to Increase Image Contrast

  • If the original image was recorded without image processing, it would be relatively low contrast as we see on the left. This is because of the wide dynamic range and linear response of digital receptors.

  • This is desirable as it is what gives us the wide range of exposure response.


Processing to increase image contrast1

Processing to Increase Image Contrast

  • The digital receptor is not limited by the narrow response of film.

  • The usual procedure is to use processing as illustrated here to increase the contrast for some portion of the exposure range.

  • The processing simulates a high contrast film image.


Processing to increase image contrast2

Processing to Increase Image Contrast

  • We do not generally use high contrast for chest radiography because it produces an image with too much area contrast (like the dark lungs shown here).


Processing a chest image

Processing a Chest Image

  • Here is a LUT processing that is more appropriate for chest radiography.

  • In general it simulates an image recorded on a latitude type film used for chest radiography.


Processing the chest image

Processing the Chest Image

  • Compare the high contrast processing to the latitude processing. The later has good object and anatomical structure contrast and visibility throughout the image.


Brightness scale inversion

Brightness Scale Inversion

  • Many radiologists find value in having an inverted (black bone) image in addition to the conventional (white bone) image at the time of viewing.

  • Some objects and structures may be more visible and easier to detect on the inverted image.

  • The inversion can be done with this type LUT.


Digital image windowing

Digital Image Windowing

  • The ability to window is a valuable feature of all digital images.

  • Windowing is a process of selecting some segment of the total pixel value (dynamic range of the receptor) and then displaying the pixel values within that segment over the full brightness (shades of gray) range from white to black.


Digital image windowing1

Digital Image Windowing

  • Contrast will be visible only for pixels within the selected window.

  • All pixel values that are either above or below the window will be either all black or all white.


Digital image windowing2

Digital Image Windowing

  • The person controlling the window can adjust both the center and width of the window.

  • The combination of these two parameters will determine the range of pixel values that will be displayed with contrast in the image.


Effect of changing the window level

Effect of Changing the Window Level

  • One of the advantages of windowing is that it makes it possible to display and enhance the contrast in selected segments of the total pixel value range. This is compared to not being able to adjust contrast on the processed film image.


Effect of changing the window level1

Effect of Changing the Window Level

  • With windowing we can create many displayed images each focusing on a specific range of pixel values.


Effect of changing the window level2

Effect of Changing the Window Level

  • When the window is set for the lower pixel range we can enhance contrast in the medistimum.

  • When set for the upper range of pixel values, the lung is enhanced.


Enhancing visibility of detail

Enhancing Visibility of detail

  • The Blurred Mask Subtraction is often used in digital radiography, to enhance the visibility of detail in certain clinical procedures.

  • This does not un-blur an image and recover detail that was completely lost because of blurring from the focal spot, motion of the receptor. What it does do is to increase the visibility (contrast) of some objects where the visibility is limited by the large area contrast such as in the chest.


Enhancing visibility of detail1

Enhancing Visibility of detail

  • The process consists of two distinct steps.

  • First a blurred copy of the original image is produced.

    • A common method is to average the pixel values in the pixel’s area.

    • This results in a blurred image that removes all detail from the image.


Enhancing visibility of detail2

Enhancing Visibility of detail

  • Now we have two images.

    • The original image contains the general large area contrast background plus some detail.

    • The blurred image contains only the large area contrast background.

  • The final step is the computer reduces the large area contrast background in relation to the contrast of detail.


Enhancing visibility of detail3

Enhancing Visibility of detail

  • The final result is that the contrast and visibility of the detail (small objects and structures) is enhanced.


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