Medical Applications with Disentanglements First MICCAI Workshop, MAD 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings /
Medical Applications with Disentanglements First MICCAI Workshop, MAD 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings / [electronic resource] :
edited by Jana Fragemann, Jianning Li, Xiao Liu, Sotirios A. Tsaftaris, Jan Egger, Jens Kleesiek.
- 1st ed. 2023.
- X, 127 p. 40 illus., 26 illus. in color. online resource.
- Lecture Notes in Computer Science, 13823 1611-3349 ; .
- Lecture Notes in Computer Science, 13823 .
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.
9783031250460
10.1007/978-3-031-25046-0 doi
Image processing--Digital techniques.
Computer vision.
Artificial intelligence.
Computer engineering.
Computer networks .
Computers.
Application software.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Computer Vision.
Artificial Intelligence.
Computer Engineering and Networks.
Computing Milieux.
Computer and Information Systems Applications.
TA1501-1820 TA1634
006
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.
9783031250460
10.1007/978-3-031-25046-0 doi
Image processing--Digital techniques.
Computer vision.
Artificial intelligence.
Computer engineering.
Computer networks .
Computers.
Application software.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Computer Vision.
Artificial Intelligence.
Computer Engineering and Networks.
Computing Milieux.
Computer and Information Systems Applications.
TA1501-1820 TA1634
006