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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, cartea 13823

Editat de Jana Fragemann, Jianning Li, Xiao Liu, Sotirios A. Tsaftaris, Jan Egger, Jens Kleesiek
en Limba Engleză Paperback – feb 2023
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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Specificații

ISBN-13: 9783031250453
ISBN-10: 3031250451
Pagini: 127
Ilustrații: X, 127 p. 40 illus., 26 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.2 kg
Ediția:1st ed. 2023
Editura: Springer Nature Switzerland
Colecția Springer
Seria Lecture Notes in Computer Science

Locul publicării:Cham, Switzerland

Cuprins

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.