Digital Imaging and Communications in Medicine (DICOM)

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Chapter 6 Medical Images in DICOM
image with 1024×1024 = 1,048,576 pixels. So, when you zoom this image to
full screen, where do the extra 1,048,576 – 65,536 = 983,040 pixels come from?
They are generated by an interpolation algorithm (usually bicubic interpolation)
and inserted between the original image pixels, thus making the image
matrix larger. As a result, when you zoom in on a digital image, you see progressively
more pixels that were not present in the original data but are added
by the interpolation. For example, out of each 4×4 = 16 pixels in the 4×-zoomed
image only one comes from the original image, and the other 15 are essentially
created by a program (Fig. 25); a substantial addition, isn’t it? At least a much
more substantial change in the image data than any reasonable lossy compression
would do.
This dominance of the artificial pixels explains why image interpolation
should be taken very seriously by all PACS developers and users, and a good
amount of research continues in this area. Because the interpolating program
has no access to the original object (patient) to make a better image, it has to
cleverly “fake” all the extra pixels so that they look as natural as possible. The
quality of this “faking” should be extraordinary and can always be used to judge
the quality of image viewing software. To test a PACS viewing workstation that
you might consider buying, load a small image (such as MR or NM), zoom in
on it and check for tiles, jaggies, broken lines, and other unnatural-looking
artifacts. If you see any of these problems, they are most definitely coming from
poor interpolation, and you are looking at a very cheap approximation of the
required standard quality. Figure 26 demonstrates this difference for a small
NM image; the interpolation on the left is extremely poor and the one on the
right is much more natural.
Interpolation does have another artifact that is impossible to avoid. When
an image is zoomed in too much (as in the example shown in Fig. 26) you will
start seeing some blur. This merely reflects the fact that interpolation does not
add information to the image and cannot add any fine, sharp details. Hence another
conclusion: do not spend your money on an expensive, super-high reso-
Fig. 25 A 4X interpolation. “T” stands for original (true) pixels, and “I” stand for interpolated
pixels