Statistical and Computational Methods in Brain Image Analysis
暫譯: 腦影像分析中的統計與計算方法

Chung, Moo K.

Statistical and Computational Methods in Brain Image Analysis
  • 出版商: CRC
  • 出版日期: 2024-10-14
  • 售價: $2,230
  • 貴賓價: 9.5 折 $2,119
  • 語言: 英文
  • 頁數: 432
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1032919957
  • ISBN-13: 9781032919959

    • 海外代購書籍(需單獨結帳)

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商品描述

The massive amount of nonstandard high-dimensional brain imaging data being generated is often difficult to analyze using current techniques. This challenge in brain image analysis requires new computational approaches and solutions. But none of the research papers or books in the field describe the quantitative techniques with detailed illustrations of actual imaging data and computer codes. Using MATLAB(R) and case study data sets, Statistical and Computational Methods in Brain Image Analysis is the first book to explicitly explain how to perform statistical analysis on brain imaging data.

The book focuses on methodological issues in analyzing structural brain imaging modalities such as MRI and DTI. Real imaging applications and examples elucidate the concepts and methods. In addition, most of the brain imaging data sets and MATLAB codes are available on the author's website.

By supplying the data and codes, this book enables researchers to start their statistical analyses immediately. Also suitable for graduate students, it provides an understanding of the various statistical and computational methodologies used in the field as well as important and technically challenging topics.

商品描述(中文翻譯)

大量非標準的高維度腦部影像數據的生成，常常使得使用當前技術進行分析變得困難。這一腦部影像分析的挑戰需要新的計算方法和解決方案。然而，該領域的研究論文或書籍中，並沒有詳細說明實際影像數據和計算機代碼的定量技術。《Statistical and Computational Methods in Brain Image Analysis》是第一本明確解釋如何對腦部影像數據進行統計分析的書籍，使用了MATLAB(R)和案例研究數據集。

本書專注於分析結構性腦部影像模態（如MRI和DTI）中的方法論問題。真實的影像應用和範例闡明了這些概念和方法。此外，大多數腦部影像數據集和MATLAB代碼可在作者的網站上獲得。

通過提供數據和代碼，本書使研究人員能夠立即開始他們的統計分析。該書同樣適合研究生，提供了對該領域中各種統計和計算方法的理解，以及重要且技術挑戰性話題的介紹。

作者簡介

Moo K. Chung, Ph.D. is an associate professor in the Department of Biostatistics and Medical Informatics at the University of Wisconsin-Madison. He is also affiliated with the Waisman Laboratory for Brain Imaging and Behavior. He has won the Vilas Associate Award for his applied topological research (persistent homology) to medical imaging and the Editor's Award for best paper published in Journal of Speech, Language, and Hearing Research. Dr. Chung received a Ph.D. in statistics from McGill University. His main research area is computational neuroanatomy, concentrating on the methodological development required for quantifying and contrasting anatomical shape variations in both normal and clinical populations at the macroscopic level using various mathematical, statistical, and computational techniques.

作者簡介(中文翻譯)

Moo K. Chung, Ph.D. 是威斯康辛大學麥迪遜分校生物統計與醫學資訊系的副教授。他同時也隸屬於威斯曼腦成像與行為實驗室。他因其應用拓撲研究（持續同調）在醫學影像方面的貢獻而獲得Vilas Associate Award，並因在《語音、語言與聽力研究期刊》（Journal of Speech, Language, and Hearing Research）上發表的最佳論文而獲得編輯獎。Chung博士在麥吉爾大學獲得統計學博士學位。他的主要研究領域是計算神經解剖學，專注於使用各種數學、統計和計算技術，開發量化和對比正常與臨床人群在宏觀層面上解剖形狀變異所需的方法論。

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