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GPUs a ‘Game Changer’ for Nuking Noise in Nuclear Imaging
- robert_foss 8y agobcaulfield: Are you a nVidia employee? You've been spamming 'groundbraking' news about nVidia for days. https://news.ycombinator.com/submitted?id=bcaulfield https://news.ycombinator.com/submitted?id=bcaulfield
- CoolGuySteve 8y agoA quick google shows that he's the 'chief blogger' for NVidia. IMO this kind of astroturfing shouldn't be allowed without some kind of disclaimer even if the content is pretty interesting. There should at least be something in his bio about it.
- deleted 8y ago[deleted]
- etaioinshrdlu 8y agoNVIDIA is great at social media marketing and puts a lot of effort into it. But it is advertising and it is not good for communities at all.
- dang 8y agoThat's not astroturfing. It's ok on HN to submit your own stuff as long as it's mixed with a variety of other material that you ran across and personally found interesting. Using HN only to submit own material is less cool, but not something we necessarily ban users for. The community tends to frown on and flag such submissions though. bcaulfield is obviously a legit HN user. The proportion is probably too heavily on the Nvidia side, but that doesn't mean he should be hounded off HN either.
- PaulHoule 8y agoWhat I find funny about this is that there was a huge concern about image compression algorithms introducing artifacts into medical images that would affect diagnosis back in the 1980s, and even to this day. Deep networks can learn to hallucinate rather well. I'm sure that they can fill in what body structures are supposed to look like (they've seen them many times) but not sure if they would help in diagnosis -- or if they would add plausible-looking details that would breed complacency.
- mhneu 8y agoThis is just a way to calculate a statistical distribution over possible body structures given an image. If the image is bad, the estimates will be bad. Hopefully the probabilities of error are carefully quantified. Edit: speeding up the MC estimates of absorbed dose, etc, (i.e. speeding the treatment planning process) seems like a much more clear improvment.
- TTPrograms 8y agoThe article explains that this is about better forward models for the measurement process rather than priors on body structure. This makes sense for systems with more complex measurement physics that common reconstructions approximate (eg. CT, PET).