Deep Generative Models [electronic resource] : Third MICCAI Workshop, DGM4MICCAI 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings / edited by Anirban Mukhopadhyay, Ilkay Oksuz, Sandy Engelhardt, Dajiang Zhu, Yixuan Yuan.
Contributor(s): Mukhopadhyay, Anirban [editor.]
| Oksuz, Ilkay [editor.] | Engelhardt, Sandy [editor.] | Zhu, Dajiang [editor.] | Yuan, Yixuan [editor.] | SpringerLink (Online service).
Material type: 
BookSeries: Lecture Notes in Computer Science: 14533Publisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edition: 1st ed. 2024.Description: XI, 248 p. 86 illus., 76 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031537677.Subject(s): Computer vision | Machine learning | Education -- Data processing | Application software | Computer Vision | Machine Learning | Computers and Education | Computer and Information Systems ApplicationsAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.37 Online resources: Click here to access online Methods -- Applications -- Methodology. Causal inference. Latent interpretation. Generative factor analysis -- Mammography. Vessel imaging -- Surgical Videos.
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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