Andere Kunden interessierten sich auch für
![Machine Learning for Medical Image Reconstruction]( "Machine Learning for Medical Image Reconstruction")
Machine Learning for Medical Image Reconstruction37,99 €![Interpretable and Annotation-Efficient Learning for Medical Image Computing]( "Interpretable and Annotation-Efficient Learning for Medical Image Computing")
Interpretable and Annotation-Efficient Learning for Medical Image Computing37,99 €![Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis]( "Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis")
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis37,99 €![Machine Learning for Medical Image Reconstruction]( "Machine Learning for Medical Image Reconstruction")
Machine Learning for Medical Image Reconstruction41,99 €![Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis]( "Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis")
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis48,99 €![Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures]( "Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures")
Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures37,99 €![Predictive Intelligence in Medicine]( "Predictive Intelligence in Medicine")
Predictive Intelligence in Medicine37,99 €
This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The workshop was held virtually.
The 15 papers presented were carefully reviewed and selected from 18 submissions. The papers are organized in the following topical sections: deep learning for magnetic resonance imaging and deep learning for general image reconstruction.
The 15 papers presented were carefully reviewed and selected from 18 submissions. The papers are organized in the following topical sections: deep learning for magnetic resonance imaging and deep learning for general image reconstruction.