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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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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...

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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 Nature Switzerland 2023.
Cham Imprint: Springer 2023.
Edition:1st ed. 2023.
Series:Lecture Notes in Computer Science 13823
DOI:10.1007/978-3-031-25046-0
Subjects:
Konferenzschrift
Pathologie
Medizinische Informatik
Online Access:Resolving-System, lizenzpflichtig: https://doi.org/10.1007/978-3-031-25046-0
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Author Notes:edited by Jana Fragemann, Jianning Li, Xiao Liu, Sotirios A. Tsaftaris, Jan Egger, Jens Kleesiek
Description
Summary: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 β-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.
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 reviewed and cover generative adversarial networks (GAN), variational autoencoders (VAE) and normalizing-flow architectures as well as a wide range of medical applications, like brain age prediction, skull reconstruction and unsupervised pathology disentanglement.
Physical Description:Online Resource
ISBN:9783031250460
DOI:10.1007/978-3-031-25046-0

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