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Medical applications with disentanglements: First MICCAI Workshop, MAD 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022 :proceedings

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This book constitutes the post-conference proceedings of the First MICCAI Workshop on Medical Applications with Disentanglements, MAD 2022, held in conjunction with MICCAI 2022, in Singapore, on September22, 2022.The 8 full papers presented in this book together with one short paper were carefully r...

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Bibliographic Details
Corporate Authors: MICCAI MAD Workshop, Singapur; Online (Author) , International Conference on Medical Image Computing and Computer Assisted Intervention (Other)
Other Authors: Fragemann, Jana (Editor) , Li, Jianning (Editor) , Liu, Xiao (Editor) , Tsaftaris, Sotirios A. (Editor) , Egger, Jan (Editor) , Kleesiek, Jens Philipp (Editor)
Format: Article (Journal) Conference Paper
Language:English
Published: Cham Springer [2023]
Series:Lecture notes in computer science 13823
In: Lecture notes in computer science (13823)

Volumes / Articles: Show Volumes / Articles.
Subjects:
Konferenzschrift
Pathologie
Medizinische Informatik
Online Access:Verlag, Cover: http://www.dietmardreier.de/annot/4B56696D677C7C39363236323039367C7C434F50.jpg?sq=1
Inhaltsverzeichnis: https://www.gbv.de/dms/tib-ub-hannover/1833347498.pdf
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Author Notes:Jana Fragemann, Jianning Li, Xiao Liu, Sotirios A. Tsaftaris, Jan Egger, Jens Kleesiek (eds.)
Table of Contents:
  • Applying Disentanglement in the Medical Domain: An Introduction.- HSIC-InfoGAN: Learning Unsupervised Disentangled Representations by Maximising Approximated Mutual Information.- Implicit Embeddings via GAN Inversion for High Resolution Chest Radiographs.- Disentangled Representation Learning for Privacy-Preserving Case-Based Explanations.- Instance-Specific Augmentation of Brain MRIs with Variational Autoencoder.- Low-rank and Sparse Metamorphic Autoencoders for Unsupervised Pathology Disentanglement.- Training beta-VAE by Aggregating a Learned Gaussian Posterior with a Decoupled Decoder.- Disentangling Factors of Morpholigical Variation in an Invertible Brain Aging Model.- A study of representational properties of unsupervised anomaly detection in brain MRI.

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