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Cross Attention Transformers for Multi-modal Unsupervised Whole-Body PET Anomaly Detection
Cancers can have highly heterogeneous uptake patterns best visualised in positron emission tomography. These patterns are essential to detect, diagnose, stage and predict the evolution of cancer. Due to this heterogeneity, a general-purpose cancer detection model can be built using unsupervised lear...
Tallennettuna:
| Julkaisussa: | Deep Gener Model (2022) |
|---|---|
| Päätekijät: | , , , , , , |
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
2022
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7616582/ https://ncbi.nlm.nih.gov/pubmed/39404690 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-031-18576-2_2 |
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