Name: Deep Learning and Convolutional Neural Networks for Medical Image Computing: Precision Medicine, High Performance and Large-Scale Datasets (en Inglés)
SKU: 49594884
Price: 2730.18 MXN
Availability: InStock
Author: Lu, Le ; Zheng, Yefeng ; Carneiro, Gustavo
ISBN: 9783319429984

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

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

Formato

Libro Físico

Editorial

Springer

Autor

Lu, Le ; Zheng, Yefeng ; Carneiro, Gustavo

Idioma

Inglés

N° páginas

326

Encuadernación

Tapa Dura

Dimensiones

24.4x16.7x2.4 cm

Peso

0.71 kg.

ISBN13

9783319429984

Categorías

Medicina preclínica: ciencias básicas
Matemáticas aplicadas
Aplicaciones gráficas y multimedia
Inteligencia artificial

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

Lu, Le ; Zheng, Yefeng ; Carneiro, Gustavo (Autor) · Springer · Tapa Dura

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Reseña del libro "Deep Learning and Convolutional Neural Networks for Medical Image Computing: Precision Medicine, High Performance and Large-Scale Datasets (en Inglés)"

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.