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Hi Howard,In my case studies rarely change once they are added. I put a caching proxy in front of orthanc and it did the trick after the first slow access. There's alot of metadata in a MRI study. I've seen 10's of MB of JSON metadata in some of our studies, which seems impressive. I suppose even with an SSD, reading out all of those files to get that volume of metadata each time is still slow.At some point in the future, I may need to investigate what metadata is really needed in my case and see if there is a way to convince Orthanc to store those in its index DB and also the dicomweb plugin to only serve those out. I've seen some interesting code comments in the dicomweb plugin in this area suggesting that there could be a configuration parameter some day to adjust the cost vs. spec compliance tradeoff of the output.Cheers,
Chris
On Oct 3, 2019, at 6:37 PM, Lander, Howard Michael <how...@renci.org> wrote:
Hi Chris.
Thanks much for the reply. The postgres filesystem is on an SSD. Is there some faster way of going about this? I tried to configure postgres to load everything into memory, but it didn't seem to help.
Howard
From: Chris McGee <cmc...@macadamian.com>
Sent: Thursday, October 3, 2019 5:08:17 PM
To: Lander, Howard Michael <how...@renci.org>
Cc: Orthanc Users <orthanc-users@googlegroups.com>
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Hello,
Sébastien-
Chris
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Thanks Sebastien !
If Extrapolate mode is used, the plugin will read up to 3 DICOM instances at random that belong to the study/series of interest. It will then test whether the majority of these instances share the same value for a predefined subset of DICOM tags. If so, this value is added to the metadata response; otherwise, the tag is not reported. In other words, this mode extrapolates the value of some predefined tags by assuming that these tags should be constant across all the instances of the study/series. This mode is a compromise between MainDicomTags (focus on speed) and Full (focus on accuracy).