Deep Learning and Convolutional Neural Networks for Medical Image Computing

Name: Deep Learning and Convolutional Neural Networks for Medical Image Computing
Brand: Springer International Publishing AG
SKU: 9783319827131
Price: 879.27 RON
Availability: InStock

Precision Medicine, High Performance and Large-Scale Datasets

Autor: Le Lu, Yefeng Zheng, Gustavo Carneiro, Lin Yang

Limbă:

Legare: Carte broșată

Editura: Springer International Publishing AG

Disponibilitate: În depozitul extern

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879.27 lei

This book presents a detailed review of the state of the art in deep learning approaches for semanti...

Informații despre carte

Autor

Le Lu, Yefeng Zheng, Gustavo Carneiro, Lin Yang

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2018

Pagini

326

EAN

9783319827131

Enbook ID

20118842

Editura

Springer International Publishing AG

Greutate

580

Dimensiuni

232 x 155 x 25

Descriere completă

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.

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Deep Learning and Convolutional Neural Networks for Medical Image Computing

Precision Medicine, High Performance and Large-Scale Datasets

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Descriere completă

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