1 option
Domain Adaptation and Representation Transfer : 5th MICCAI Workshop, DART 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings / edited by Lisa Koch, M. Jorge Cardoso, Enzo Ferrante, Konstantinos Kamnitsas, Mobarakol Islam, Meirui Jiang, Nicola Rieke, Sotirios A. Tsaftaris, Dong Yang.
SpringerLink Books Lecture Notes In Computer Science (LNCS) (1997-2024) Available online
View online- Format:
- Book
- Author/Creator:
- Koch, Lisa.
- Series:
- Lecture Notes in Computer Science, 1611-3349 ; 14293
- Language:
- English
- Subjects (All):
- Image processing--Digital techniques.
- Image processing.
- Computer vision.
- Application software.
- Machine learning.
- Computers.
- Information technology--Management.
- Information technology.
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Computer and Information Systems Applications.
- Machine Learning.
- Computing Milieux.
- Computer Application in Administrative Data Processing.
- Local Subjects:
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Computer and Information Systems Applications.
- Machine Learning.
- Computing Milieux.
- Computer Application in Administrative Data Processing.
- Physical Description:
- 1 online resource (180 pages)
- Edition:
- 1st ed. 2024.
- Place of Publication:
- Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
- Summary:
- This book constitutes the refereed proceedings of the 5th MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2023, which was held in conjunction with MICCAI 2023, in October 2023. The 16 full papers presented in this book were carefully reviewed and selected from 32 submissions. They discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains. .
- Contents:
- Domain adaptation of MRI scanners as an alternative to MRI harmonization
- MultiVT: Multiple-Task Framework for Dentistry
- Black-Box Unsupervised Domain Adaptation for Medical Image Segmentation
- PLST: A Pseudo-Labels with a Smooth Transition Strategy for Medical Site Adaptation
- Compositional Representation Learning for Brain Tumor Segmentation
- Hierarchical Compositionality in Hyperbolic Space for Robust Medical Image Segmentation
- Realistic Data Enrichment for Robust Image Segmentation in Kidney Transplant Pathology
- Boosting Knowledge Distillation via Random Fourier Features for Prostate Cancer Grading in Histopathology Images
- Semi-supervised Domain Adaptation for Automatic Quality Control of FLAIR MRIs in a Clinical Data Warehouse
- Towards Foundation Models Learned from Anatomy in Medical Imaging via Self-Supervision
- The Performance of Transferability Metrics does not Translate to Medical Tasks
- DGM-DR: Domain Generalization with Mutual Information Regularized Diabetic Retinopathy Classification
- SEDA: Self-Ensembling ViT with Defensive Distillation and Adversarial Training for robust Chest X-rays Classification
- A Continual Learning Approach for Cross-Domain White Blood Cell Classification
- Metadata Improves Segmentation Through Multitasking Elicitation
- Self-Prompting Large Vision Models for Few-Shot Medical Image Segmentation.
- Notes:
- Description based on publisher supplied metadata and other sources.
- Other Format:
- Print version: Koch, Lisa Domain Adaptation and Representation Transfer
- ISBN:
- 9783031458576
- 3031458575
- OCLC:
- 1405938472
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.