* Implement capabilities: https://www.dicomstandard.org/using/dicomweb/capabilities/
  from https://groups.google.com/d/msgid/orthanc-users/c60227f2-c6da-4fd9-9b03-3ce9bf7d1af5n%40googlegroups.com?utm_medium=email&utm_source=footer

* /rendered at study level shall return all instances, not only one (https://groups.google.com/g/orthanc-users/c/uFWanYhV8Fs/m/ezi1iXCXCAAJ)
  Check /rendered at series level too.

* Implement serialization of DicomWeb jobs

* Add support for application/zip in /dicom-web/studies/ (aka sup 211: https://www.dicomstandard.org/docs/librariesprovider2/dicomdocuments/news/ftsup/docs/sups/sup211.pdf?sfvrsn=9fe9edae_2)

* Based on this discussion: https://discourse.orthanc-server.org/t/series-metadata-retrieval-is-very-long-even-with-configuration-optimization/3389 
  optimize studies/.../series/.../metadata route when "SeriesMetadata" is set 
  to "MainDicomTags" and "ExtraMainDicomTags" are configured according to recommandation 
  (from this setup: https://bitbucket.org/osimis/orthanc-setup-samples/src/master/docker/stone-viewer/docker-compose.yml).
  
  with a 600 instance series with SQLite - all timings are performed without verbose logs !!!!:
  - time curl http://localhost:8043/dicom-web/studies/1.2.276.0.7230010.3.1.2.1215942821.4756.1664826045.3529/series/1.2.276.0.7230010.3.1.3.1215942821.4756.1664833048.11984/metadata > /dev/null 
    -> 883ms in Full mode
    -> 565ms in MainDicomTags mode     

    -> 545ms in Full mode with 1 worker
    -> 335ms in Full mode with 2 workers
    -> 267ms in Full mode with 3 workers
    -> 270ms in Full mode with 4 workers
    -> 270ms in Full mode with 8 workers


  - note that all measurements have been performed on a DB with a single series !  We should repeat 
    that with a more realistic DB

  with a 3 series study (11 + 1233 + 598 instances)
  time curl http://localhost:8043/dicom-web/studies/1.2.276.0.7230010.3.1.2.1215942821.4756.1664826045.3529/metadata > /dev/null 
    -> 1.355ms in Full mode before using worker threads
    ->   700ms in Full mode with 4 workers