CT image preprocessing in python?
From my experience in working with soft tissue CT medical images, I have seen CT having -1024 intensity for air and up to +3000 intensity for cancellous bone. When it comes to metal-like electrodes and even tooth images, it reaches up to +9000. So I guess for heavy metals like car engines the intensity value of 52000 is not aberration(though I never heard CT images of car engines so far!).
Pre-processing can include windowing or normalization operations and noise removals. Windowing is something already mentioned here to restructure the intensity range to a more workable one.
I have a 3D CT image of a car engine in raw form with no header information. When loaded into numpy array as 16 bit unsigned integer, I noticed that the values range between 0 to 52000. Is this normal for a CT Image? When viewing the image, I also noticed a lot of cloud like noise in every slice. I'm trying to extract features using a deep learning method. This is my first time working with CT Images. What pre processing is neccesary for such CT Images?