Computer Vision for Microscopy Image Analysis

Chen, Mei

  • 出版商: Academic Press
  • 出版日期: 2020-12-04
  • 售價: $4,020
  • 貴賓價: 9.5$3,819
  • 語言: 英文
  • 頁數: 350
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 0128149728
  • ISBN-13: 9780128149720
  • 相關分類: Computer Vision 電腦視覺

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商品描述

High-throughput microscopy enables researchers to acquire thousands of images automatically over a short time, making it possible to conduct large-scale, image-based experiments for biological or biomedical discovery. However, visual analysis of large-scale image data is a daunting task. The post-acquisition component of high-throughput microscopy experiments calls for effective and efficient computer vision techniques.

Computer Vision for Microscopy Image Analysis provides a comprehensive and in-depth introduction to state-of-the-art computer vision techniques for microscopy image analysis, demonstrating how they can be effectively applied to biological and medical data.

The reader of the book will learn:

  • How computer vision analysis can automate and enhance human assessment of microscopy images for discovery
  • The important steps in microscopy image analysis
  • State-of-the-art methods for microscopy image analysis including machine learning and deep neural network approaches

This reference on the state-of-the-art computer vision methods in microscopy image analysis is suitable for researchers and graduate students interested in analyzing microscopy images or for developing toolsets for general biomedical image analysis applications.

  • Each topic contains a comprehensive overview of the field, followed by in-depth presentation of a state-of-the-art approach
  • Perspectives and content contributed by both technologists and biologists
  • Tackles specific problems of detection, segmentation, classification, tracking, cellular event detection
  • Contains the fundamentals of object measurement in microscopy images
  • Contains open source data and toolsets for microscopy image analysis on an accompanying website

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