Recent Advances in Deep Learning for Medical Image Analysis: Paradigms and Applications
暫譯: 醫學影像分析中的深度學習最新進展：範式與應用

Chen, Yen-Wei, Lin, Lanfen, Jain, Rahul Kumar

Recent Advances in Deep Learning for Medical Image Analysis: Paradigms and Applications
  • 出版商: Springer
  • 出版日期: 2025-10-02
  • 售價: $7,890
  • 貴賓價: 9.5 折 $7,496
  • 語言: 英文
  • 頁數: 274
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 3031947908
  • ISBN-13: 9783031947902
  • 相關分類: DeepLearning

    • 海外代購書籍(需單獨結帳)

商品描述

This book is a valuable resource for understanding the transformative role of artificial intelligence in modern healthcare and aims to inspire continued research and collaboration across disciplines. In recent years, deep learning has emerged as a transformative technology across various fields, with medical image analysis standing out as one of its most impactful applications. This book offers a comprehensive overview of the latest developments in this fast-evolving domain, bridging foundational principles with state-of-the-art techniques that are redefining the future of medical imaging.

This book is structured in two parts--Part I: Deep Learning Fundamentals and Paradigms and Part II: Advanced Deep Learning for Medical Image Analysis. The book provides in-depth coverage of essential topics, including convolutional neural networks, attention mechanisms, transformer architectures, multimodal analysis, semi-supervised learning, domain adaptation, generative models, and foundation models for large-scale pretraining.

This book is intended for a broad audience, including graduate students, academic researchers, and industry professionals in computer science, biomedical engineering, and healthcare technologies. It serves as both an introductory guide and a reference resource for those seeking to deepen their knowledge in this rapidly evolving area.

商品描述(中文翻譯)

這本書是理解人工智慧在現代醫療保健中轉型角色的寶貴資源，旨在激勵跨學科的持續研究與合作。近年來，深度學習已成為各個領域中的一項變革性技術，其中醫學影像分析脫穎而出，成為其最具影響力的應用之一。本書提供了這個快速發展領域最新進展的全面概述，將基礎原則與重新定義醫學影像未來的最先進技術相結合。

本書分為兩個部分——第一部分：深度學習基礎與範式，第二部分：醫學影像分析的進階深度學習。本書深入探討了多個重要主題，包括卷積神經網絡（convolutional neural networks）、注意力機制（attention mechanisms）、變壓器架構（transformer architectures）、多模態分析（multimodal analysis）、半監督學習（semi-supervised learning）、領域適應（domain adaptation）、生成模型（generative models）以及大型預訓練的基礎模型（foundation models）。

本書的目標讀者範圍廣泛，包括研究生、學術研究人員以及計算機科學、生物醫學工程和醫療技術領域的行業專業人士。它既是一本入門指南，也是希望在這個快速發展領域中深化知識的參考資源。

作者簡介

Prof. Yen-Wei Chen received his B.E. degree in 1985 from Kobe University, Kobe, Japan. He received his M.E. degree in 1987 and his D.E. degree in 1990, both from Osaka University, Osaka, Japan. From 1991 to 1994, he was a research fellow at the Institute of Laser Technology, Osaka. From October 1994 to March 2004, he was an associate professor and a professor in the Department of Electrical and Electronic Engineering, University of the Ryukyus, Okinawa, Japan. He is currently a professor at the college of Information Science and Engineering, Ritsumeikan University, Japan. Since April 2024, he has been a Foreign Fellow of the Engineering Academy of Japan. He is associate editors for the International Journal of Image and Graphics (IJIG), and the International Journal of Knowledge-based Intelligent Engineering Systems. His research focuses on computer vision, deep learning and medical image analysis. He has published more than 300 research papers in these fields.

Prof. Lanfen Lin received her B.S. and Ph.D. degrees from Northwestern Polytechnical University in 1990, and 1995 respectively. She held a postdoctoral position with the department of Computer Science and Technology, Zhejiang University, China, from January 1996 to December 1997. She was an associate professor from 1998 to 2005. Now she is a full professor and the vice director of the Artificial Intelligence Institute in Zhejiang University. She is also a member of Zhejiang Key Laboratory of Multi-omics Precision Diagnosis and Treatment of Liver Diseases.Her research interests include computer vision, medical image processing, and intelligent manufacturing. She has published more than 200 research papers in these fields.

Dr. Rahul Kumar Jain received his Ph.D. degree from Ritsumeikan University, Shiga, Japan, in 2022. He has been an intern trainee at Tiwaki Co., Ltd., Japan, since 2019. He is now working as a senior researcher at the College of Information Science and Engineering, Ritsumeikan University, Japan. His research interests include computer vision, deep learning, and image processing as well as the applications of Artificial Intelligence in areas including engineering, science, computer science, healthcare, and so on.

作者簡介(中文翻譯)

陳彥維教授於1985年獲得日本神戶大學的工學士學位。1987年獲得日本大阪大學的碩士學位，1990年獲得博士學位。1991年至1994年，他在大阪的激光技術研究所擔任研究員。1994年10月至2004年3月，他在日本琉球大學電氣電子工程系擔任副教授及教授。目前，他是日本立命館大學資訊科學與工程學院的教授。自2024年4月起，他成為日本工程學會的外籍院士。他是《國際影像與圖形期刊》（International Journal of Image and Graphics, IJIG）及《國際基於知識的智能工程系統期刊》的副編輯。他的研究專注於計算機視覺、深度學習及醫學影像分析，並在這些領域發表了300多篇研究論文。

林蘭芬教授於1990年和1995年分別獲得西北工業大學的學士及博士學位。她於1996年1月至1997年12月在中國浙江大學計算機科學與技術系擔任博士後研究員。1998年至2005年，她擔任副教授。現在她是浙江大學人工智慧研究所的正教授及副所長，並且是浙江省多組學科精準診斷與治療肝病重點實驗室的成員。她的研究興趣包括計算機視覺、醫學影像處理及智能製造，並在這些領域發表了200多篇研究論文。

賈胡爾·庫馬爾·賈因博士於2022年獲得日本立命館大學的博士學位。自2019年以來，他在日本的Tiwaki有限公司擔任實習生。現在他在日本立命館大學資訊科學與工程學院擔任高級研究員。他的研究興趣包括計算機視覺、深度學習及影像處理，以及人工智慧在工程、科學、計算機科學、醫療等領域的應用。

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