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One of the first things AI will be really good at will be image post processing. Even then I, in case of medical diagnosis, I'd prefer to have an actual person

by hef19898 4y ago

One of the first things AI will be really good at will be image post processing. Even then I, in case of medical diagnosis, I'd prefer to have an actual person compare the "RAW" image to whatever the AI came up with. Simply because post processing can create artifacts that can throw you of quite a bit. Regarding tue quality of imaging: I tend to agree, and the better imaging gets the more we will have to relly on humans to judge whether or not treatment is necessary or recommended. That judgement alone is, IMHO, in the same league as full self driving and requires general AI.

lostlogin 4y ago
The raw image is not good and isn’t usable. AI denoises and this is what makes it usable. Then it doubles the resolution. There is no point in reviewing the raw image as it doesn’t add anything. A study is generally 300-1000 images. If you’re going to review the raw and therefore look at 600-2000 images you’ve just wasted everything AI gained and you might as well not use it. I acquire the images and I look at what I get and re-run anything that’s got artifact. This is not unusual and generally happens due to movement, excessive image noise or incorrect parameter selection. I don’t review the raw, but I do review the output. Keep in mind that MR images have always been very heavily processed at every stage of image formation as any way of squeezing more out the the acquisition will have time benefits. There are a ton of ways a tech can create a misleading or faulty image with parameter selection which leads to an incorrect diagnosis. This could happen quite easily and AI being part of any error m is not something that keeps me awake at night, unlike other other parameters with which I have seen mistakes and have made them myself.
- hef19898 4y ago
  Thanks for the explanation! Shows that some knowledge in digital photography doesn't translate into other domains taking pictures. Comments like yours are what I love about HN!

lostlogin 4y ago

The raw image is not good and isn’t usable. AI denoises and this is what makes it usable. Then it doubles the resolution. There is no point in reviewing the raw image as it doesn’t add anything. A study is generally 300-1000 images. If you’re going to review the raw and therefore look at 600-2000 images you’ve just wasted everything AI gained and you might as well not use it. I acquire the images and I look at what I get and re-run anything that’s got artifact. This is not unusual and generally happens due to movement, excessive image noise or incorrect parameter selection. I don’t review the raw, but I do review the output. Keep in mind that MR images have always been very heavily processed at every stage of image formation as any way of squeezing more out the the acquisition will have time benefits. There are a ton of ways a tech can create a misleading or faulty image with parameter selection which leads to an incorrect diagnosis. This could happen quite easily and AI being part of any error m is not something that keeps me awake at night, unlike other other parameters with which I have seen mistakes and have made them myself.

hef19898 4y ago
Thanks for the explanation! Shows that some knowledge in digital photography doesn't translate into other domains taking pictures. Comments like yours are what I love about HN!