Clinical image-based procedures, distributed and collaborative learning, artificial intelligence for combating COVID-19 and secure and privacy-preserving machine learning [E-Book] : 10th Workshop, CLIP 2021, Second Workshop, DCL 2021, First Workshop, LL-COVID19 2021, and First Workshop and Tutorial, PPML 2021, held in Conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021, Proceedings / edited by Cristina Oyarzun Laura, M. Jorge Cardoso, Michal Rosen-Zvi, Georgios Kaissis, Marius George Linguraru, Raj Shekhar, Stefan Wesarg, Marius Erdt, Klaus Drechsler, Yufei Chen, Shadi Albarqouni, Spyridon Bakas, Bennett Landman, Nicola Rieke, Holger Roth, Xiaoxiao Li, Daguang Xu, Maria Gabrani, Ender Konukoglu, Michal Guindy, Daniel Rueckert, Alexander Ziller, Dmitrii Usynin, Jonathan Passerat-Palmbach
This book constitutes the refereed proceedings of the 10th International Workshop on Clinical Image-Based Procedures, CLIP 2021, Second MICCAI Workshop on Distributed and Collaborative Learning, DCL 2021, First MICCAI Workshop, LL-COVID19, First Secure and Privacy-Preserving Machine Learning for Med...
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Personal Name(s): | Albarqouni, Shadi, editor |
Bakas, Spyridon, editor / Cardoso, M. Jorge, editor / Chen, Yufei, editor / Drechsler, Klaus, editor / Erdt, Marius, editor / Gabrani, Maria, editor / Guindy, Michal, editor / Kaissis, Georgios, editor / Konukoglu, Ender, editor / Landman, Bennett, editor / Li, Xiaoxiao, editor / Linguraru, Marius George, editor / Oyarzun Laura, Cristina, editor / Passerat-Palmbach, Jonathan, editor / Rieke, Nicola, editor / Rosen-Zvi, Michal, editor / Roth, Holger, editor / Rueckert, Daniel, editor / Shekhar, Raj, editor / Usynin, Dmitrii, editor / Wesarg, Stefan, editor / Xu, Daguang, editor / Ziller, Alexander, editor | |
Edition: |
1st edition 2021 |
Imprint: |
Cham :
Springer,
2021
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Physical Description: |
XXV, 190 pages 78 illustrations, 67 illustrations in color (online resource) |
Note: |
englisch |
ISBN: |
9783030908744 |
DOI: |
10.1007/978-3-030-90874-4 |
Series Title: |
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Image processing, computer vision, pattern recognition, and graphics ;
12969 /* Depending on the record driver, $field may either be an array with "name" and "number" keys or a flat string containing only the series name. We should account for both cases to maximize compatibility. */?> Lecture notes in computer science |
Subject (LOC): |
- Intestine segmentation with small computational cost for diagnosis assistance of ileus and intestinal obstruction
- Generation of Patient-Specific, Ligamentoskeletal, Finite Element Meshes for Scoliosis Correction Planning
- Bayesian Graph Neural Networks For EEG-based Emotion Recognition
- ViTBIS: Vision Transformer for Biomedical Image Segmentation
- Attention-guided pancreatic duct segmentation from abdominal CT volumes
- Development of the Next Generation Hand-Held Doppler With Waveform Phasicity Predictive Capabilities Using Deep Learning
- Learning from mistakes: an error-driven mechanism to improve segmentation performance based on expert feedback
- TMJOAI: an artificial web-based intelligence tool for early diagnosis of the Temporomandibular Joint Osteoarthritis
- COVID-19 Infection Segmentation from Chest CT Images Based on Scale Uncertainty
- Multi-task Federated Learning for Heterogeneous Pancreas Segmentation
- Federated Learning in the Cloud for Analysis of Medical Images - Experience with Open Source Frameworks
- On the Fairness of Swarm Learning in Skin Lesion Classification
- Lessons learned from the development and application of medical imaging-based AI technologies for combating COVID-19: why discuss, what next
- The Role of Pleura and Adipose in Lung Ultrasound AI
- DuCN: Dual-children Network for Medical Diagnosis and Similar Case Recommendation towards COVID-19
- Data imputation and reconstruction of distributed Parkinson's disease clinical assessments: A comparative evaluation of two aggregation algorithms
- Defending Medical Image Diagnostics against Privacy Attacks using Generative Methods: Application to Retinal Diagnostics.