However, even I could tell there was something wrong with my left hip (besides the fact that I couldn't walk more than a half block) - the line corresponding to cartilage thickness was about 1/10th the size of the other hip.
This, perhaps, could have been flagged by a simple comparative algorithm and passed on to the radiologist before s/he looked at the image. The difference in itself might not have been significant - we all have asymmetries in our bodies - but it would have merited a second look.
But I got a reading 'mild arthritis in left hip' - while an MRI three months later came up with 'severe arthritis in left him including bone marrow edema.'
Granted, MRI results often overstate artiritic changes in joints but these results do not compute.
Yes, Infervision CEO also talked about "traditional computer-aided machine vision programs, such as R2." Those have been around for a couple of decades, he said, as the wiki entry you posted shows. The question now becomes how a new generation of deep learning-based screening would stack up against human doctors.
Hi! You might be onto something here. I can see how AI/Deep Learning would be useful in "filtering" information, but a lot of things doctors have to decide on -- in terms of diagnosis -- are judgment calls, I think.
How would a machine learn those borderline cases? Machine can be only as good as judgement calls doctors made previously, because everything machines learn is based on data they are fed with.
I had an x-ray taken of my left hip in 2010 - the radiologist's report came up 'mild arthritis in left hip.'
I took a copy to an Orthopod MD I knew - outside my insurance network so I paid in cash (this is the USA - Land of the Free) - and she said 'your left hip is trashed' (or something like that). It took me six months to convince my medical insurance to get a left hip replacement.
Incredible results - improved my life 10^2.
So, what use an arbitrary human radiologist? Some know their stuff, some are hacks in it for the money.
But the more apropos question is 'What use is a "deep learning" radiologist?'