CODEWITHSUNDEEP
image-processingdeep-learningartificial-intelligencedata-processing
Geoffrey Bourque-Riel
Geoffrey Bourque-Riel

Reputation: 41

Is pixel value normalization needed in medical image segmentation?

I have a dataset of CT-Scan representing hips scan. I'm currently not normalizing the pixel value because in CT-Scan pixel value represent different part of the scan (bone 1000+, water0, air-1000, etc). Also the range of pixels value change every scan (ex. -500:1500, -400:1200). I'm wondering if normalizing pixel value between [0,1] would be a + for my training or I would lost information on the relation between int pixel value and segmentation truth. Thanks for the answers

Upvotes: 3

Views: 620

Answers (1)

code-lukas
code-lukas

Reputation: 1651

It depends a little on your data. What you are describing are so called Hounsfield Units (probably read up on that), you basically express every intensity relative to the one of water.

Bone density (and with that the corresponding intensity) can vary greatly, not to mention if there is metal present. Your HU range is highly dependent on the body region and mainly the patient.

https://images.app.goo.gl/WNLCs8eENTdbXWwM7

CT Scans are usually uint16 grayscale, I would definitely normalize as long as you can ensure that your float range is sufficient to accommodate the 2^16 different grayscale values.

Upvotes: 2

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