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{ "item_title" : "Deep Learning in Medical Image Analysis", "item_author" : [" Yu-Dong Dong Zhang", "J. M. Górriz", "Zhengchao Dong "], "item_description" : "The accelerating power of deep learning in diagnosing diseases will empower physicians and speed up decision making in clinical environments. Applications of modern medical instruments and digitalization of medical care have generated enormous amounts of medical images in recent years. In this big data arena, new deep learning methods and computational models for efficient data processing, analysis, and modeling of the generated data are crucially important for clinical applications and understanding the underlying biological process. This book presents and highlights novel algorithms, architectures, techniques, and applications of deep learning for medical image analysis.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/3/03/651/469/3036514694_b.jpg", "price_data" : { "retail_price" : "107.30", "online_price" : "107.30", "our_price" : "107.30", "club_price" : "107.30", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Deep Learning in Medical Image Analysis|Yu-Dong Dong Zhang

Deep Learning in Medical Image Analysis

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Overview

The accelerating power of deep learning in diagnosing diseases will empower physicians and speed up decision making in clinical environments. Applications of modern medical instruments and digitalization of medical care have generated enormous amounts of medical images in recent years. In this big data arena, new deep learning methods and computational models for efficient data processing, analysis, and modeling of the generated data are crucially important for clinical applications and understanding the underlying biological process. This book presents and highlights novel algorithms, architectures, techniques, and applications of deep learning for medical image analysis.

Details

  • ISBN-13: 9783036514697
  • ISBN-10: 3036514694
  • Publisher: Mdpi AG
  • Publish Date: August 2021
  • Dimensions: 9.61 x 6.69 x 1.38 inches
  • Shipping Weight: 2.6 pounds
  • Page Count: 458

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