1. Images provided by Ohio University’s Witmer Lab for STEM educational aids for K–12 Researchers conducted a CT scan of the head of a 41-year-old male white rhino (named Kehtla). A CT scanner is a big machine, looks much like a doughnut that passes over the object to scan while it takes 100s of pictures. His head was so big, it had to be scanned in sections and then the images were assembled into a single 3D representation. Can you imagine how many pixels it takes to represent Kehtla’s head?

2. The pictures from a CT scan are black, white, and grey instead of just black and white like we discussed in the previous activity; so they will take more information to store. To represent a grey image (called greyscale), each pixel is has a value to represent the “intensity” of the pixel. In other words, what shade of grey is that pixel? Greyscale uses a range from a minimum of 0 (black) to a maximum number (for example, the max can be 255) to represent white. Quiz this: If each image of a CT scan is typically 512 pixels by 512 pixels and you had 500 images, how many pixels would it take to store the 3D representation?

3. Images provided by Ohio University’s Witmer Lab for STEM educational aids for K–12 After scanning a rhino head, scientists used this greyscale image to see the inside of the horns and how they are made. The CT images of the horns give a clear picture of how the middle of the rhino horn is more dense, which is represented by the darker pixels than the outside portions which tend to get worn off. Scientists were able to see why their horns have that sharp pointed shape. Now we can see that Rhino horns sort of work like a pencil!

4. Images provided by Ohio University’s Witmer Lab for STEM educational aids for K–12 You can even assign colors to the CT images of the horns to get a more clear picture of how they are made. On this colored image, the more red colors represent the denser portions. See how cool it is to use Medical Imaging Data to discover new things! There is so much that can be made possible when you combine Computer Science, Computer Vision, Mathematics, and Medicine.