Draft:Contrastive Multimodal Image Representation for Registration (CoMIR)

Submission declined on 11 February 2025 by KylieTastic (talk).

This draft's references do not show that the subject qualifies for a Wikipedia article. In summary, the draft needs multiple published sources that are:

in-depth (not just passing mentions about the subject)
reliable
secondary
independent of the subject

Make sure you add references that meet these criteria before resubmitting. Learn about mistakes to avoid when addressing this issue. If no additional references exist, the subject is not suitable for Wikipedia.

If you would like to continue working on the submission, click on the "Edit" tab at the top of the window.
If you have not resolved the issues listed above, your draft will be declined again and potentially deleted.
If you need extra help, please ask us a question at the AfC Help Desk or get live help from experienced editors.
Please do not remove reviewer comments or this notice until the submission is accepted.

Where to get help

If you need help editing or submitting your draft, please ask us a question at the AfC Help Desk or get live help from experienced editors. These venues are only for help with editing and the submission process, not to get reviews.
If you need feedback on your draft, or if the review is taking a lot of time, you can try asking for help on the talk page of a relevant WikiProject. Some WikiProjects are more active than others so a speedy reply is not guaranteed.

How to improve a draft

Wikipedia:Contributing to Wikipedia – a basic overview on how to edit Wikipedia.
Help:Wikitext – how to use the markup
Help:Referencing for beginners – how to include references
Wikipedia:Article development – how to develop your article
Wikipedia:Writing better articles – how to improve your article
Wikipedia:Verifiability – make sure your article includes reliable third-party sources

You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article.

Improving your odds of a speedy review

To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags.

Add tags to your draft

Editor resources

Easy tools: Citation bot (help) | Advanced: Fix bare URLs

Declined by KylieTastic 3 months ago. Last edited by KylieTastic 3 months ago. Reviewer: Inform author.

Resubmit

Please note that if the issues are not fixed, the draft will be declined again.

Contrastive Multimodal Image Representation for Registration (CoMIR) is a deep learning framework designed to align images from different modalities by transforming them into a shared representational space. The framework archives this using contrastive learning that maximizes the similarity between image representations of aligned multimodal image pairs.^[1] These image representations can be used with any typical intensity-based image registration method.

References

^ Lu, Jiahao; Pielawski, Nicki; Wetzer, Emil; Öfverstedt, Johan; Wählby, Carolina; Lindblad, Joakim; Sladoje, Natasa (2022). "Is image-to-image translation the panacea for multimodal image registration? A comparative study". PLOS ONE. 17 (11): e0276196. doi:10.1371/journal.pone.0276196. Retrieved 11 February 2025.{{cite journal}}: CS1 maint: unflagged free DOI (link)

[Lu2022-1] Lu, Jiahao; Pielawski, Nicki; Wetzer, Emil; Öfverstedt, Johan; Wählby, Carolina; Lindblad, Joakim; Sladoje, Natasa (2022). "Is image-to-image translation the panacea for multimodal image registration? A comparative study". PLOS ONE. 17 (11): e0276196. doi:10.1371/journal.pone.0276196. Retrieved 11 February 2025.{{cite journal}}: CS1 maint: unflagged free DOI (link)

[1]