from images to answers a basic understanding of digital imaging and analysis
TRANSCRIPT
What is an Image?
Computers store data and understand data in numerical form. We can say that a digital image is a numerical representation of a “picture” – a set of numbers interpreted by the computer which creates a visual representation that is understood by humans.
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244 198 179123 94 19532 43 5213 32 11
253 217 23468 185 9713 12 2711 14 26
Pixels are identified by their position in a grid (two-dimensional array), referenced by its row (x), and column (y).
The Pixel Array
Pixel- A “picture element”.Each element contains spatialand intensity information.
Bitmaps
At each pixel position the image is sampled and quantified. An integer representing the brightness or darkness of the image is generated for each pixel This integer. A collection of these gray values is called a bitmap.
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210 104 0 0 123 234
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Resolution
Image Resolution- Overall image qualitySpatial Resolution- Pixel size, image magnificationBrightness Resolution- Pixel depthOptical Resolution- Lens characteristics
How Big Is a Pixel?
Dynamic Range
How many gray levels between the darkest and brightest areas
8-bit 28 = 256 gray values
12-bit 212 = 4,096 gray values
16-bit 216 = 65,536 gray values
What components are involved in imaging?
Input device- the source of the images; camera, microscope, etc.
Interface hardware- the connection between the input device and the computer.
Imaging software- the user interface to all the imaging components.
Output devices- printers, image storage devices, monitors.
The Analytical Imaging Process
Sample Preparation- Sectioning, staining, labeling, etc.
Acquisition- how do we acquire an image into the computer?
Enhancement- how do we make it look better to extract information?
Identification- which attributes of the image are we interested in?
Measurement- what information can we obtain?
Report Generation- how can we present this information?
Archive- how can we store the information?
Acquisition
After sample preparation, acquisition is the most importantaspect of image analysis.
Has the specimen been prepared properly?
Is the imaging apparatus properly set up?• Kohler Illumination for Microscopes• Clean Optics• Color cameras should be color-balanced• Monochrome cameras should have dark-field subtraction• Good dynamic range should be established in the image• For fluorescence images- turn OFF autoexposure
Image Enhancement
There are basic ways to enhance an image: • Modify its intensity index: brightness, contrast, gamma• Background correction• Apply a spatial filter or arithmetic operation
And advanced enhancement methods:• Manipulate the image frequencies: fast fourier transform• Morphological transformations: erode, dilate
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Histogram Stretch
Low Dynamic Range- Medium Contrast
Full Dynamic Range- Good Contrast
Spatial filters change the look of an image and are divided into two categories.
Convolution Filters:
• Low-pass- Blurs or smoothes an object
• Sharpen- Enhances all intensity transitions
• Median- Removes random impulse noise
Morphological Filters:
• Edge Detection- highlights edges
• Erosion- Makes objects smaller
• Dilation- Makes objects larger
Spatial Filtering
Once the attributes of an image are enhanced and clearly visible, identification can be done as follows:
• Thresholding techniques- allowing the software to identify objects, based on intensity variations from background or other objects using either grayscale or color intensities
• Area of Interest (AOI)- manually defining the objects
Object Identification
Grey Scale Threshold
The overall objective of thresholding is to extract the objects of interest- to distinguish them from other objects or background.
• Size
• Shape
• Intensity/Integrated Optical Density
• Populations
• Statistics
Once objects are identified, we are dealing with a set of pixels, which are a set of numbers. We are then able to measure anything we need such as
Measurement Parameters
Using intensity transitions it is possible to measure thicknesses of objects. Edge tracing tools may be employed to do this:
Thickness Measurements
Specialized Measurements
Specialized measurements may be made with standard image analysis tools-
• Colocalization
• Object Tracking
• FRET Analysis
• Ratiometric Imaging
Dynamic Data Exchange (DDE)- Sending data to Excel for further statistical analysis
Data Collection- Collection of analysis data from multiple images into a single space, which can then be sent elsewhere or used to create reports
Report Generation- Custom templates used to create standardized reports.
Data Output
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