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Medical Applications with Disentanglements : First MICCAI Workshop, MAD 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings / edited by Jana Fragemann, Jianning Li, Xiao Liu, Sotirios A. Tsaftaris, Jan Egger, Jens Kleesiek.
SpringerLink Books Lecture Notes In Computer Science (LNCS) (1997-2024) Available online
View online- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Lecture notes in computer science 1611-3349 ; 13823
- Lecture Notes in Computer Science, 1611-3349 ; 13823
- Language:
- English
- Subjects (All):
- 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.
- Local Subjects:
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Computer Vision.
- Artificial Intelligence.
- Computer Engineering and Networks.
- Computing Milieux.
- Computer and Information Systems Applications.
- Physical Description:
- 1 online resource (X, 127 pages) : 40 illustrations, 26 illustrations in color.
- Edition:
- 1st ed. 2023.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer Nature Switzerland : Imprint: Springer, 2023.
- System Details:
- text file PDF
- Summary:
- 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.
- Contents:
- 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.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-031-25046-0
- 9783031250460
- Access Restriction:
- Restricted for use by site license.
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