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Titlebook: Deep Learning and Convolutional Neural Networks for Medical Image Computing; Precision Medicine, Le Lu,Yefeng Zheng,Lin Yang Book 2017 Spr

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發(fā)表于 2025-3-21 16:51:39 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Deep Learning and Convolutional Neural Networks for Medical Image Computing
副標(biāo)題Precision Medicine,
編輯Le Lu,Yefeng Zheng,Lin Yang
視頻videohttp://file.papertrans.cn/265/264590/264590.mp4
概述Addresses the challenges of applying deep learning for medical image analysis.Presents insights from leading experts in the field.Describes principles and best practices.Includes supplementary materia
叢書名稱Advances in Computer Vision and Pattern Recognition
圖書封面Titlebook: Deep Learning and Convolutional Neural Networks for Medical Image Computing; Precision Medicine,  Le Lu,Yefeng Zheng,Lin Yang Book 2017 Spr
描述.This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database..
出版日期Book 2017
關(guān)鍵詞Deep Learning; Convolutional Neural Networks; Medical Image Analytics; Computer-Aided Diagnosis; Hospita
版次1
doihttps://doi.org/10.1007/978-3-319-42999-1
isbn_softcover978-3-319-82713-1
isbn_ebook978-3-319-42999-1Series ISSN 2191-6586 Series E-ISSN 2191-6594
issn_series 2191-6586
copyrightSpringer International Publishing Switzerland 2017
The information of publication is updating

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