2. Digital Fluoroscopy PPT created by: Jed Miles, BSRS, RT(R), CRT-CA
Radiologic Science for Technologist, 9th Ed.
By: Stewart Bushong, Scd, FAAPM, FACR
Principals of Radiographic Imaging, 5th Ed.
By: Richard Carlton,M.S ., RT(R)(CV), FAEIRS &
Arlene Adler, M.Ed., RT(R), FAEIRS
Digital Radiography an Introduction
By: Euclid Seeram, RT(R), BSc, MSc, FCAMRT
PPT created by: Jed Miles, BSRS, RT(R), CRT-CA

3. Objectives Describe various attributes of the digital image
Describe the parts of a digital imaging system
Explain critical elements used to create a digital fluoroscopy image
Discuss limitations inherent in currently available digital radiography systems
Explain why digital radiography systems have greater latitude than conventional fluoroscopy systems

4. Objective - cont
Discuss image display options of digital fluoroscopy systems

5. History of Digital Fluoroscopy

6. Pioneering Days
1896: Thomas Edison developed the first direct viewing fluoroscope using glass coated with calcium tungstate
Resulted in a faint image only viewable with scotopic (night) vision
Once hazards of direct viewing of fluoro image became known, a design change placed glass plate in a lead lined box
Viewing the optical image took place via lenses and mirrors
1948: Image Intensification Tubes were developed
Resulted in being able to view the image using photopic (day) vision

7. Pioneering Days
1970’s: Medical physics groups pioneered digital image output with conventional image intensified fluoro
Required a computer being placed between the television camera tube and the television monitor
1980’s: Digital Subtraction Angiography (DSA) systems gained acceptance by medical community
1983: CCD Camera began replacing TV camera tubes
2000’s: Dynamic flat panel detectors replaced image intensification tube in fluoroscopy

8. The Digital Image A Brief Review

9. Digital Image Characteristics
Digital Image consists of pixels that represent the original image arranged in a matrix format
Pixels
Size determines the spatial resolution
Bit depth determines scale of contrast
Matrix
Created by pixels arranged into rows and columns
Matrix size determined by numbers of pixels

10. The Pixel The Pixel is the smallest element in a digital image
Pixel size determines the spatial resolution of image
Smaller pixels increases visibility of smaller structures
Increases recorded detail
Pixel size is related to matrix size and size of image intensifier surface area being utilized
Smaller pixel size will result in a larger matrix size
Larger matrix size will result in increased spatial resolution
Pixel bit depth
Determines the numbers of shades of gray to be displayed
Increased bit depth results in more shades of gray

11. Pixel Size
Size matters: A digital fluoro system typically uses a 1024 x 1024 image matrix
Sometimes referred to as a 1000-line system
Digital fluoro spatial resolution is determined by both the image matrix and by the input size of the image intensifier being utilized
Larger matrix size results = increased spatial resolution
Smaller input size utilization = increased spatial resolution

12. Pixel Size: Let’s do the Math…!
Formula: Pixel size = Image Intensifier size / matrix
Q: What is the pixel size of a 1000-line DF system operating in a 6-inch mag mode?
Conversion factors:
6 inches x 25.4 mm/inch = mm
1000-line system = 1024 x 1024 matrix
A: mm / 1024 = mm

13. Pixel Bit Depth Pixel bit depth aka bits per pixel (bpp)
Determines the number of gray shades or brightness levels available for image display by each pixel
The numerical value of each pixel determines its brightness level

14. Pixel Bit Depth
Number of gray shades or brightness levels is determined by the bit depth (2n)
Where “n” is the number of bits (brightness levels) available for each pixel
12 bit depth (212) will produce an image consisting of each pixel within the matrix being able to produce 4096 shades of gray or brightness levels
2 shades
64 shades
256 shades
1 Bit (21)
6 Bit (26)
8 Bit (28)

15. The Matrix Image Matrix
Consists of pixels arranged into rows and columns
Size of pixels and pixel density determine spatial resolution
4 X 4
8 X 8
16 X 16
32 x 32
64 X 64
512 X 512

16. Spatial Resolution Spatial resolution
Describes the ability to resolve two objects in close proximity
Smaller pixel size will result increased spatial resolution*
Increased spatial resolution enables increased visibility of smaller objects and detail
*Spatial resolution is not related the amount of exposure
Pixel size determines spatial resolution
Exposure is related to the ‘visibility’ of spatial resolution and detail
Object: Line pair phantom
Image: Line pair phantom

17. Signal to Noise Ratio (SNR)
Describes the amount of image forming signal to inherent noise in any electronic system
Other descriptors are used
Signal difference to noise ratio
Subject contrast also known as contrast-to-noise ratio (CNR)
The image above has a sufficiently high SNR to clearly separate the image information from background noise
A low SNR would produce an image where the "signal" and noise are more comparable and thus harder to discern from one another

18. Digital File Size Matrix (pixel density) Pixel Bit depth
Digital data requires hard drive file space for display, archive and retrieval
Digital Image file size is affected by
Matrix (pixel density)
Larger matrix size will increase data file size
512 x 512 = 262,144 pixels, x 1024 = 1,048,576 pixels
Doubling the matrix size will quadruple the numbers of pixels
Pixel Bit depth
Increasing pixel bit depth results in larger data file size

19. Digital File Size Image format
Image file size is correlated to the compression algorithm used to compress the original pixel data.
Images can be compressed in various ways
Compression uses an algorithm that stores an exact representation or an approximation of the original image in a smaller number of bytes that can be expanded back to its uncompressed form with a corresponding decompression algorithm.
Considering different compressions available for use, it is common for two images of the same number of pixels and bit depth to have a very different compressed file size
Lossless image compression results in larger file sizes with no loss of resolution
Lossy image compression results in smaller file sizes with resulting loss of resolution
This loss of resolution can range from a small to large amount

20. Lossless Versus Lossy Compression Algorithm