Deep Learning and Convolutional Neural Networks for Medical Image Computing

Name: Deep Learning and Convolutional Neural Networks for Medical Image Computing
Brand: Springer Nature
SKU: 9783319429991
Availability: InStock

Best Price (Coupon Required):
Buy Deep Learning and Convolutional Neural Networks for Medical Image Computing for $125.10 at @ Link.springer.com when you apply the 10% OFF coupon at checkout.
Click “Get Coupon & Buy” to copy the code and unlock the deal.

Set a price drop alert to never miss an offer.

1 Offer Price Range: $139.00 - $139.00

BEST PRICE

Single Product Purchase

$125.10

@ Link.springer.com with extra coupon

Price Comparison

Seller	Contact Seller	List Price	On Sale	Shipping	Best Promo	Final Price	Volume Discount	Financing	Availability	Seller's Page
BEST PRICE 1 Product Purchase @ Link.springer.com		$139.00	$139.00		10% OFF This deals requires coupon	$125.10		See Site	In stock	Visit Store

Product Details

Brand

Springer Nature

Manufacturer

N/A

Part Number

GTIN

9783319429991

Condition

New

Product Description

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.

Available Colors

N/A

Available Sizes

N/A