Medical Applications with Disentanglements (eBook, PDF)

First MICCAI Workshop, MAD 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings
Redaktion: Fragemann, Jana; Kleesiek, Jens; Egger, Jan; Tsaftaris, Sotirios A.; Liu, Xiao; Li, Jianning

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 127
• Erscheinungstermin: 31. Januar 2023
• Englisch
• ISBN-13: 9783031250460
• Artikelnr.: 67382417

Inhaltsangabe

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.