Test files repository and dicom_parser's GitHub address #13
Replies: 6 comments 13 replies
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By @ matthew.brett on July 23, 2021, 4:26pm Yes, it would be very good to collate some data. Yes, I agree that it would be sensible to avoid having much code. The way we play it in Nibabel is to have many data repositories pulled in as submodules, for testing. There's some documentation here, but you've probably already seen it. We could collect relatively small single or several study repositories, with suitable licences, and then have a repository that contains a set of useful data repositories as submodules to define test suites. I don't think it much matters where these repositories go, as long as the licences are open - we can always move them around later. But it might be good to make an organization with a good name to encapsulate the idea that it's a cross-language cross-package effort to share work about DICOM parsing. What do you think? |
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By @ thewtex on July 24, 2021, 11:10am DICOM testing dataset resources, already in Git and Datalad: |
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By @ neurolabusc on July 27, 2021, 12:32pm Can I suggest you consider validation datasets that do not require a lot of disk space, provide validated conversion and are designed to illustrate corner cases that could confuse a converter. Meeting these specifications allows one to include automated regression testing that can be applied to each commit. For example, dcm2niix includes several dcm_qa repositories as submodules and uses Travis to automatically test each commit to detect any changes in conversion results. I may certainly be biased, but I would think it would be great if the community could use and extend the repositories currently used with dcm2niix. These simple repositories can help assure conformance across tools. The current datasets have been specifically designed to test corner cases:
You may also want to look at exemplars of diffusion, archival and unusual sequences. These are generally much larger datasets than the dcm_qa test modules, but do exhibit unique properties. You may also want to look at the old rosetta bit project that provides data from several vendors. |
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By @ baratzz on July 28, 2021, 1:37pm @ neurolabusc thank you so much for these fantastic resources! I opened a new GitHub organization (Open DICOM), I think I'll move dicom_parser there in a few days after neurohackademy is over and I finish some WIP. It certainly seems like the
Does this make sense? I don't have any experience managing large files with Git. |
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By @ msz on July 28, 2021, 5:28pm Hi, I've been following this discussion and also spoke to @ baratzz about this matter. The dcm_qa repositories look very well curated, so big thank you for the links and detailed explanations. I have a question which is slightly tangential. I was wondering if there is a relation between the dcm_qa's and the DataLad repository linked previously? There doesn't seem to be, judging by looking at some file names. If the one at datasets.datalad.org is out of date, do you think it would be worthwile to ceate a new datalad dataset with all the dcm_qa's attached (I am not an expert, so not quite sure how to set this up, but this seems possible)? And consequently, would that be any use for that in setting up a testing environment (e.g. using datalad to only get the desired sub-datasets)? Though probably adding the chosen ones as submodules would do just as well. |
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By @ neurolabusc on August 9, 2021, 4:29pm I have created a few extra dcm_qa_* repositories to illustrate edge cases:
I also cleaned up the links to other sources for diverse DICOM datasets. |
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By @ baratzz on July 23, 2021, 4:17pm
@ matthew.brett, @ effigies, @ moloney, @ chafey
Hi again,
I started thinking about creating the independent test files repository and a few things came to mind:
Image
andSeries
instantiation. Not really a concern at the moment, I know, just a thought.I would be happy to hear your thoughts.
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