Medical Applications with Disentanglements : First MICCAI Workshop, MAD 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings
1st ed. 2023
Book Details
Format
Paperback / Softback
Book Series
Lecture Notes in Computer Science
ISBN-10
3031250451
ISBN-13
9783031250453
Edition
1st ed. 2023
Publisher
Springer International Publishing AG
Imprint
Springer International Publishing AG
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Feb 1st, 2023
Print length
127 Pages
Product Classification:
Medical bioinformaticsComputer visionImage processing
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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 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.
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.
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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