Thoracic Imaging 2003 - Society of Thoracic Radiology

TUESDAY
184
Digital Images: Camera to Powerpoint
Eric J. Stern, M.D.
University of Washington School of Medicine, Department of Radiology
Harborview Medical Center, Seattle, Washington
The use of digital images has become more commonplace,
especially with the ability to obtain images directly from a picture
archival and communication system (PACS) or low cost
digital cameras. For many academic radiologists, using these
digital images for slides is a relatively new and potentially
intimidating process. It is important to be able to use digital
images effectively and efficiently, creating a visually optimized
image while keeping the file size appropriate to its application.
For such optimal use, not all digital images are created equally.
I will focus on how to optimize your use of digital images for
electronic presentation.
Definitions
Pixel dimensions
A digital image is composed of a two dimensional array of
pixels (picture elements), similar to dots on a newspaper photograph
or grains on a photographic print, arranged according to a
predefined ratio of columns and rows. Each pixel represents a
portion of the image in a particular color, or shade of gray. The
pixel dimensions of an image (e.g. 600 x 800, 1024 x 768, 1200
x 1600, etc) define the information content of the image. The
more pixels there are in an image, the more information is contained
within it.
Image “size”
Image size is a slippery and often misused term. When one
speaks of a “large” image, one could be referring to an image
with a large pixel dimension (e.g., 2000 x 3000), one with a
large file size (requires a lot of storage space on a hard disk), or
a large physical size (e.g., 3 x 4 feet). Because of this large
potential for confusion, I greatly prefer the terms “pixel dimensions,”
“file size,” or “physical size” over the easily misused
term “image size.” The image file is determined by pixel dimensions,
bit depth and the level of file compression. To determine
the file size of an uncompressed digital image, use this formula:
File size = (pixel width x pixel height) x (bit depth ÷ 8)
The result will be the file size in bytes. Divide this by 1024
to determine the size in kilobytes (Kb) (and by 1024 again if
you want the size in megabytes). For example, a 24-bit RGB
image that is 459 pixels wide and 612 pixels tall would have a
file size of 823Kb:
(459 x 612) x (24 ÷ 8) = 842,724 bytes ÷ 1024 = 823Kb
An 8 bit grey scale image that is 459 pixels wide and 612
pixels tall would have a file size of 274Kb:
(459 x 612) x (8 ÷ 8) = 280,908 bytes ÷ 1024 = 274 K
Output resolution
Output resolution is a measurement of clarity or detail of the
displayed image, and is expressed as the number of pixels displayed
per unit length. This ratio varies widely, depending on
which output device one is using. On a computer monitor, it is
usually expressed in terms of dots per inch (dpi) or pixels per
inch (ppi). The output resolutions of typical computer monitors
range between 72 and 100 dpi.
For example, consider an image with pixel dimensions of
1200 x 1800 pixels which is to be output to both a computer
screen with an output resolution of 100 dpi and a laser printer
with an output resolution of 600 dpi. On the computer screen,
the physical size of the image will be 12 X 18 inches. On the
laser print, the physical size of the image will be 2 x 3 inches.
Both images have the same pixel dimension, and hence the
same information content.
For another example, imagine that you need a new computer
monitor with a 20 inch wide screen. After shopping around,
you narrow down your decision to two monitors, differing only
in output resolution: one will display 1200 x 800 pixels and the
other will display 1800 x 1200. The first monitor will have an
image resolution of 1200/20 or 60 dpi, while the second monitor
will have a resolution of 1800/20 or 90 dpi.
Software and hardware requirements
One can choose from a number of programs for optimizing
digital images. However, I use and highly recommend newer
versions of ADOBE PHOTOSHOP ® (Adobe Systems
Incorporated, San Jose CA) which is one of the most powerful
and widely-available programs for general image manipulation.
Many of the principles discussed will also apply to other software
packages.
One can use either a Macintosh (Apple, Inc. Cupertino, CA),
Windows (Microsoft Corp, Redmond, WA), or Unix-based
computer to do image manipulation. The interfaces might differ
slightly between platforms, but the concepts are the same.
Steps in image Processing
Once you have obtained a digital image, there are several
steps you can go through to optimize the image for an electronic
presentation.
Step 1: Convert to grayscale. Unless you are dealing with
true color images, most of your radiologic images should be
converted to grayscale, if they are not already. This immediately
cuts the file size by two thirds without any loss of image
quality. This is simply preformed by opening the image popdown
menu, selecting mode, then selecting grayscale.
Step 2: Crop your image as necessary, removing unwanted
or distracting data such as patient identifiers, non-pertinent body
parts, white borders, or artifacts. This will also help reduce file
size. Patient identifiers can be covered up with a box filled with
black or by cutting out the text when a black background has
been selected.
Step 3: Adjust the levels to take advantage of the entire grey
scale available. This is one of the most important steps. You can
use the auto levels function from the image pop-down menu, but
recommend fine tuning your image with the manual level
adjustment.