Hi I work in medical image processing for OCT scan. In OCT scan, we A-scan and B scan. A scan is image of eyeball and B scan is basically image of retina layers. The A and B scan are orthogonal to each other, means there are lot of scans present which constitute of number of lines on A scan. Check out this link for reference: https://core4.bmctoday.net/storage/images/issue-1988/1021_I_Fig1.png
Now, as there is spacing in individual B scan and let say we created a deep learning model for B scan, which gives us probabilities. My question is how do we project these probabilities on A scan. Has anyone done this kind of experiments for CT and MRI?