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Interpretable and Annotation Efficient Learning for Medical Image Computing

in Medical Image Computing, iMIMIC 2020, the Second International Workshop on Medical Image Learning with Less Labels and Imperfect Data, MIL3ID 2020;

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Deep Learning and Data Labeling for Medical Applications

and Expert Label Synthesis, LABELS 2016, and the Second International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2016. The 28;

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Deep Learning and Convolutional Neural Networks for Medical Image Computing

learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation;

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Deep Learning and Convolutional Neural Networks for Medical Image Computing: Precision Medicine, High Performance and Large-Scale Datasets

learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation;

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Deep Learning for Medical Image Analysis

Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This;

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Deep Network Design for Medical Image Computing

deep learning design principles for MIC and to apply them to their medical problems. Explains design principles of deep learning;

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Soft Computing Based Medical Image Analysis

extensive background for the development of intelligent systems based on soft computing used in medical image analysis and processing. The book;

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Medical Image Computing and Computer-Assisted Intervention MICCAI 2017

. Part II: optical imaging; airway and vessel analysis; motion and cardiac analysis; tumor processing; planning and simulation for medical;

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Medical Image Computing and Computer Assisted Intervention MICCAI 2017

. Part II: optical imaging; airway and vessel analysis; motion and cardiac analysis; tumor processing; planning and simulation for medical;

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Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 Part I

The three-volume set LNCS 9900, 9901, and 9902 constitutes the refereed proceedings of the 19th International Conference on Medical Image;

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Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 7-21, 2016, Proceedings, Part II

The three-volume set LNCS 9900, 9901, and 9902 constitutes the refereed proceedings of the 19th International Conference on Medical Image;

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Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2016 Part III

The three-volume set LNCS 9900, 9901, and 9902 constitutes the refereed proceedings of the 19th International Conference on Medical Image;

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Handbook of Medical Image Computing and Computer Assisted Intervention

>Demonstrates proven algorithms for a whole range of essential medical imaging applications Includes source codes for use in a plug-and-play;

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Medical Image Recognition, Segmentation and Parsing

medical image recognition, segmentation and parsing of multiple objects Efficient and effective machine learning solutions based on big;

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Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2013

have been organized in the following topical sections: image reconstruction and motion modeling; machine learning in medical image computing;

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Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics

research and literature; and describes a range of different methods that employ deep learning for object or landmark detection tasks in 2D and 3D;

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Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics

research and literature; and describes a range of different methods that employ deep learning for object or landmark detection tasks in 2D and 3D;

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Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support

in Medical Image Computing, iMIMIC 2019, and the 9th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2019, held;

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Image Analysis and Recognition

submissions. The papers are organized in the following topical sections: machine learning in image recognition; machine learning for medical image;

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Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014

The three-volume set LNCS 8673, 8674, and 8675 constitutes the refereed proceedings of the 17th International Conference on Medical Image;

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Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015

The three-volume set LNCS 9349, 9350, and 9351 constitutes the refereed proceedings of the 18th International Conference on Medical Image;

Vergelijkbare producten zoals Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015

Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015

The three-volume set LNCS 9349, 9350, and 9351 constitutes the refereed proceedings of the 18th International Conference on Medical Image;

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Medical Image Analysis and Informatics

With the development of rapidly increasing medical imaging modalities and their applications, the need for computers and computing in image;

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Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention

Expert Label Synthesis, LABELS 2019, the First International Workshop on Hardware Aware Learning for Medical Imaging and Computer Assisted;

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Computer Vision for Microscopy Image Analysis

and efficient techniques as there are not enough human resources to advance science by manual annotation.This book articulates the;

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Disruptive Trends in Computer Aided Diagnosis

classification and deep learning/machine learning techniques to design efficient computer aided diagnosis architecture. It is aimed to highlight new;

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Machine Learning Systems for Multimodal Affect Recognition

over annotation and feature extraction to post-processing, classification of individual modalities and fusion in the context of ensemble classifiers. He;

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