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ORCID1st MAD@MICCAI 2022: Singapore
- Jana Fragemann, Jianning Li, Xiao Liu, Sotirios A. Tsaftaris, Jan Egger, Jens Kleesiek:
Medical Applications with Disentanglements - First MICCAI Workshop, MAD 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings. Lecture Notes in Computer Science 13823, Springer 2023, ISBN 978-3-031-25045-3
Introduction
- Jana Fragemann, Xiao Liu, Jianning Li, Sotirios A. Tsaftaris, Jan Egger, Jens Kleesiek:
Applying Disentanglement in the Medical Domain: An Introduction for the MAD Workshop. 3-11
GAN-Based Approaches
- Xiao Liu, Spyridon Thermos, Pedro Sanchez, Alison Q. O'Neil, Sotirios A. Tsaftaris:
HSIC-InfoGAN: Learning Unsupervised Disentangled Representations by Maximising Approximated Mutual Information. 15-21 - Tobias Weber
, Michael Ingrisch, Bernd Bischl, David Rügamer:
Implicit Embeddings via GAN Inversion for High Resolution Chest Radiographs. 22-32 - Helena Montenegro, Wilson Silva, Jaime S. Cardoso:
Disentangled Representation Learning for Privacy-Preserving Case-Based Explanations. 33-45
Autoencoder-Based Approaches
- Jon Middleton, Marko Bauer, Jacob Johansen, Mads Nielsen, Stefan Sommer, Akshay Pai:
Instance-Specific Augmentation of Brain MRIs with Variational Autoencoders. 49-58 - Hristina Uzunova, Heinz Handels, Jan Ehrhardt:
Low-Rank and Sparse Metamorphic Autoencoders for Unsupervised Pathology Disentanglement. 59-69 - Jianning Li, Jana Fragemann, Seyed-Ahmad Ahmadi, Jens Kleesiek, Jan Egger:
Training β-VAE by Aggregating a Learned Gaussian Posterior with a Decoupled Decoder. 70-92
Normalizing-Flow-Based Approaches
- Matthias Wilms, Pauline Mouches, Jordan J. Bannister, Sönke Langner, Nils D. Forkert:
Disentangling Factors of Morphological Variation in an Invertible Brain Aging Model. 95-107
Comparision
- Ayantika Das, Arun Palla, Keerthi Ram, Mohanasankar Sivaprakasam:
A Study of Representational Properties of Unsupervised Anomaly Detection in Brain MRI. 111-125
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