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MR211 Unit 2 Review
Postprocessing
| Term | Definition |
|---|---|
| LUT | A list of the pixel values that make up the “ideal” histogram shape for an image of a particular body part. Can also be used during postprocessing to provide a means to adjust the contrast or grayscale necessary to adequately view the anatomic region (gradation processing) |
| Window width | Adjusts the length of gray scale in the image (contrast) |
| Window level | Adjusts the overall or average brightness of the image |
| Fourier transform | Converts image data FROM the spatial domain TO the frequency domain for processing. |
| Smoothing | Type of low-pass filtering that removes noise from an image (side effect: may increase blurriness of image). |
| Edge enhancement | Type of high-pass filtering that brings out smaller details by suppressing larger, background areas (side effect: may increase image noise). |
| Dual energy subtraction | Creates a double-exposure is made at two different kVp settings or with filters to produce separate soft tissue and bone images |
| Dose area product (DAP) | Calculates dose by multiplying entrance dose (in centigray) by exposure field sized used |
| Dose creep | The use of higher than necessary radiation dose to a patient to avoid repeats caused by underexposure |
| Saturation | Extreme over-exposure, causing a loss of data that results in a flat black appearance of the over-exposed portion of the image |
| Point processing | Processing operations that perform a specific algorithm on each pixel in sequence, pixel by pixel. Example: Subtraction |
| Area processing | Processing operations that execute a function on a local group of pixels or subsection of the image. Example: Zoom (magnification) |
| Global processing | Processing operations that carry out a massive spatial function across the entire area of the image. Examples: Rotate, invert, or translate the image |
| Tissue equalization | Software-weighted processing function whereby underexposed areas (light areas) are made darker and overexposed areas (dark areas) are made lighter. The effect is an image that appears to have lower contrast so that dense and lucent structures are better seen within the same image. |
| Unsharp mask filtering | A mask image is created which contains only the larger, gross structures in the image. A kernel is passed over the image, which has the effect of averaging local pixel values. Structures smaller than the kernel size are suppressed and no longer visible. Creating the mask image is a form of low-pass filtering. |
| Low-pass filtering | Usually “smoothing” function at the console. Cleans up noise, such as a white spot artifact from “pixel drop-out”, or mottle. Trade-off: slightly blurrier image, loss of fine edges. |
| High-pass filtering | Usually “edge enhancement” function at the console. Brings out smaller details by suppressing larger, background areas. Trade-off: slightly noisier image. Misuse of EE can also result in loss of detail. |
| Inverse Fourier transform | Mathematical function that is used to return image data FROM the frequency domain BACK to the spatial domain for viewing. |
| Alternative algorithms | A way to adjust the contrast and brightness characteristics of an image is to re-process it under a different pre-set anatomical algorithm. May interfere with PACS info for the image. |
| Region of interest (ROI) | A quantitative function of digital imaging that allows for the pixel value of a selected area of interest to be calculated. This value can then help characterize disease. |
| Dark mask/shuttering | Reverses blank areas around the image to black border. Reduces extraneous glare, improving apparent contrast. Always recommended, but should NOT take the place of proper collimation pre-exposure. |
| Image reversal | Reverses image to “black-on-white” (white background). Produces no new information in the image, but can make some details subjectively more apparent. |
| Resizing | Zoom or reduce/expand features to re-map image onto a smaller or larger matrix (automatically done to initially fit display monitor). |
| Magnification | Magnifying glass (small area of image anatomy) or zoom technique (magnification of entire image). |
| Annotation | Allows selection of preset terms and/or manual text input. Can be useful when additional information is necessary. Should not take the place of R & L lead markers. |
| Image flip | Allows for the flipping of the image so that it is oriented properly for interpretation |
| Stitching | When anatomy or the area of interest is too large to fit on one detector, multiple images can be “stitched” together using specialized software programs |
| Spatial domain | Pixels in this domain are sorted by location (example: matrix). Digital radiographs are displayed on for viewing in the spatial domain. |
| Frequency domain | Objects (details) in this domain are sorted by size (example: edge enhancement & smoothing). |
| Intensity domain | Pixels in this domain are sorted by pixel values (example: histogram). |
| Random noise | Artifacts of variable size that occur in an irregular, chaotic distribution (Example: Quantum mottle). Best removed through use of kernels. |
| Periodic noise | Artifacts that tend to be of roughly consistent size and occur in a regular pattern (Example: Electronic noise such as “snow”). Best removed through use of frequency processing. |
Created by:
KFannon
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