First Workshop DGM4MICCAI 2024 and First Workshop DALi 2024 Held in Conjunction
The First Workshop on Deep Generative Models for Medical Image Computing and Computer Assisted Intervention (DGM4MICCAI) 2024 and the First Workshop on Deep Active Learning for Medical Image Analysis (DALi) 2024 were held in conjunction with the 20th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2024).
4.7 out of 5
Language | : | English |
File size | : | 43318 KB |
Text-to-Speech | : | Enabled |
Enhanced typesetting | : | Enabled |
Print length | : | 503 pages |
Screen Reader | : | Supported |
Paperback | : | 144 pages |
Item Weight | : | 2.11 ounces |
Dimensions | : | 5.51 x 0.51 x 8.27 inches |
The DGM4MICCAI workshop brought together researchers from academia and industry to discuss the latest advances in deep generative models for medical image computing and computer assisted intervention. The workshop featured invited talks from leading experts in the field, as well as oral and poster presentations from researchers around the world.
The DALi workshop brought together researchers from academia and industry to discuss the latest advances in deep active learning for medical image analysis. The workshop featured invited talks from leading experts in the field, as well as oral and poster presentations from researchers around the world.
Both workshops were a great success, and they provided a valuable opportunity for researchers to share their latest work and to learn from each other.
DGM4MICCAI 2024
The DGM4MICCAI workshop was co-chaired by Dr. Guotai Wang of the University of California, San Francisco, and Dr. Xiaobo Li of the University of North Carolina at Chapel Hill.
The workshop featured invited talks from the following leading experts in the field:
- Dr. Guotai Wang, University of California, San Francisco
- Dr. Xiaobo Li, University of North Carolina at Chapel Hill
- Dr. Ronald M. Summers, Mayo Clinic
- Dr. Daniel Rueckert, Imperial College London
- Dr. Bernhard Kainz, Medical University of Graz
The workshop also featured oral and poster presentations from researchers around the world. The presentations covered a wide range of topics, including:
- Deep generative models for medical image synthesis
- Deep generative models for medical image segmentation
- Deep generative models for medical image registration
- Deep generative models for medical image analysis
DALi 2024
The DALi workshop was co-chaired by Dr. Huazhu Fu of the University of California, Berkeley, and Dr. Yi Zhang of the University of California, Los Angeles.
The workshop featured invited talks from the following leading experts in the field:
- Dr. Huazhu Fu, University of California, Berkeley
- Dr. Yi Zhang, University of California, Los Angeles
- Dr. Ronald M. Summers, Mayo Clinic
- Dr. Daniel Rueckert, Imperial College London
- Dr. Bernhard Kainz, Medical University of Graz
The workshop also featured oral and poster presentations from researchers around the world. The presentations covered a wide range of topics, including:
- Deep active learning for medical image segmentation
- Deep active learning for medical image classification
- Deep active learning for medical image registration
- Deep active learning for medical image analysis
The First Workshop on Deep Generative Models for Medical Image Computing and Computer Assisted Intervention (DGM4MICCAI) 2024 and the First Workshop on Deep Active Learning for Medical Image Analysis (DALi) 2024 were a great success. The workshops provided a valuable opportunity for researchers to share their latest work and to learn from each other. The workshops also helped to foster collaboration between researchers from academia and industry.
4.7 out of 5
Language | : | English |
File size | : | 43318 KB |
Text-to-Speech | : | Enabled |
Enhanced typesetting | : | Enabled |
Print length | : | 503 pages |
Screen Reader | : | Supported |
Paperback | : | 144 pages |
Item Weight | : | 2.11 ounces |
Dimensions | : | 5.51 x 0.51 x 8.27 inches |
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4.7 out of 5
Language | : | English |
File size | : | 43318 KB |
Text-to-Speech | : | Enabled |
Enhanced typesetting | : | Enabled |
Print length | : | 503 pages |
Screen Reader | : | Supported |
Paperback | : | 144 pages |
Item Weight | : | 2.11 ounces |
Dimensions | : | 5.51 x 0.51 x 8.27 inches |