Assume you collected 1 million counts in a uniform flood.

Another point of interest is that the matrix for the above image in PET is 128 whereas the CT image has a matrix of 512 CT shows that is it not part of the wall and the fused PET/CT scan helps the physician negate the PVE effect. In the above image a PET scan defines a tumor that may or may not be attached to the thoracic wall.

Here is how PVE can actually confuse the acquired data.

Likewise activity also spills into the pixel that are outside the cylinder, areas of background.

Activity spills out from the cylinder into the partial pixel(s).

This means that certain areas of the cylinder collects less counts based on the fact that only part of the pixel is collecting data.

In the exam given the actual image is circular, but pixels are squared.

The result is a lost of counts at the edge of the image's acquisition.

This is best explained by looking at the edge of a circle (above) where only part of a pixel is collecting the counts.Here is an example how how resolution is effected by matrix size and depth.Most modern cameras have the ability to collect in word mode Chances of pixel saturation is slim to none. A pixel can also be in word mode which translates to 2 8 x 2 8 = 65.5k counts/pixel.Counts in the saturated pixel roll over and start back at zero and build up again.The pixel stops acquiring, but the rest of the system continues to count or.The image stops acquiring (this is my personal experience) or.What happens if a pixel becomes saturated or counts go beyond 256?.If a matrix size is 128 x 128 x 1 byte then it means that each pixel can hold 2 8 counts or up to 256 counts.Consider 16 bit = 2 byte = 8 = 1 word.

Another issue of concern is the byte verses word mode of the pixel.

When thinking matrix you need to include the amount of counts being acquired.

The question one has to ask is which matrix is the best choice given a specific procedure? While examples are given above there is still some variation within the different choices.

Nuclear medicine matrix sizes vary and are as follows.

This information is helpful, not only in assessing resolution, but also being able to measure the size a lesion, by knowing the amount of pixels it covers.

Identification of pixel size is noted above with a 128 matrix and a camera that is 15 inches square.

Matrix size - From a planar perspective (2-D images).

Looking at nuclear cardiology displaying the LUTs, which scale would you choose?.

Here are a lot of examples of LUTs used in nuclear medicine and diagnostic radiology.

Arrange the boxes within the row to match the subtle changes in color. The first and last blocks in each row cannot be moved.

Test our ability to see minor changes in color (hue).

Understanding our Sluts and NM 'limited' resolution it can be stated that minor changes in counts per pixel may not be seen.

Yet the human eye is more sensitive to green and yellow when compared to blue and red.

The human eye can see over 1 million types of color, hence the eye is more 'sensitive' to a tricolor scale.

Therefore, given 256 shades of gray, it takes 5 shades in either direction to realize a slight change in the scale

Related to shades of gray the human eye can only see about a 2% change in brightness.

What kind of detail can we actually see?.

Example of how different color scales effect how we visually see a bone scan.

Perigees states 262,000 shades or combinations can be used, however, if each color represents 2 8 shades then there are 2 8 x 2 8 x 2 8 = 1.67 x 10 7 (red, green, and blue) combinations

This further increases the ability to find minor changes in counts when all three primary colors are used.

A blending of colors increases the amount variation between the amount of counts to pixels and the amount of color shades per count(s).

LUT combinations use up to three primary colors are Red, Green, and Blue (remember robbing?).

LUT can also be assigned to many types of color scales which may further enhance the imaged data and may improve the diagnostic quality of a study.A gray scale can also be inverted where the hottest pixel becomes black and white indicates no counts.Given the above gray scale the pixel(s) with the maximum number of counts is white (or clear) and the pixels with the least counts is black.When displaying counts from an acquisition the computer applies a Look-Up Table (LUT) that assigns counts/pixel with XY coordinates.A gray scale has 256 shades (2 8) of gray that relates to the amount of counts in an image.

This variation in counts shows a variation in the gray scale where increasing shades of gray relates to a decease in the number of counts.The above matrix shows a count value in each cell notices that it decreases in descending order with the lower right containing 50 counts and upper left at 0 counts.

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