Deep generative models: third MICCAI workshop, DGM4MICCAI 2023 : held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023 : proceedings
Methods -- Applications -- Methodology. Causal inference. Latent interpretation. Generative factor analysis -- Mammography. Vessel imaging -- Surgical Videos.
Gespeichert in:
| Körperschaft: | |
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| Weitere Verfasser: | , , , , |
| Dokumenttyp: | Konferenzschrift |
| Sprache: | Englisch |
| Veröffentlicht: |
Cham
Springer Nature Switzerland
2024.
Cham Imprint: Springer 2024. |
| Ausgabe: | 1st ed. 2024. |
| Schriftenreihe: | Lecture Notes in Computer Science
14533 |
| DOI: | 10.1007/978-3-031-53767-7 |
| Schlagworte: | |
| Online-Zugang: | Resolving-System, lizenzpflichtig: https://doi.org/10.1007/978-3-031-53767-7
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| Verfasserangaben: | Anirban Mukhopadhyay, Ilkay Oksuz, Sandy Engelhardt, Dajiang Zhu, Yixuan Yuan, editors |
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| 520 | |a This LNCS conference volume constitutes the proceedings of the third MICCAI Workshop, DGM4MICCAI 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 2023. The 23 full papers included in this volume were carefully reviewed and selected from 38 submissions. The conference presents topics ranging from methodology, causal inference, latent interpretation, generative factor analysis to applications such as mammography, vessel imaging, and surgical Videos. | ||
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