Overview
Are you a computer scientist working on image analysis? Are you a biologist seeking tools to process the microscopy data from image-based experiments? Computer Vision for Microscopy Image Analysis provides a comprehensive and in-depth discussion of modern computer vision techniques, in particular deep learning, for microscopy image analysis that will advance your efforts.Progress in imaging techniques has enabled the acquisition of large volumes of microscopy data and made it possible to conduct large-scale, image-based experiments for biomedical discovery. The main challenge and bottleneck in such experiments is the conversion of ""big visual data"" into interpretable information.Visual analysis of large-scale microscopy data is a daunting task. Computer vision has the potential to automate this task. One key advantage is that computers perform analysis more reproducibly and less subjectively than human annotators. Moreover, high-throughput microscopy calls for effective and efficient techniques as there are not enough human resources to advance science by manual annotation.This book articulates the strong need for biologists and computer vision experts to collaborate to overcome the limits of human visual perception, and devotes a chapter each to the major steps in analyzing microscopy images, such as detection and segmentation, classification, tracking, and event detection.
Full Product Details
Author: Mei Chen (Principal Research Manager, Microsoft, Redmond, Washington, USA)
Publisher: Elsevier Science Publishing Co Inc
Imprint: Academic Press Inc
Weight: 0.480kg
ISBN: 9780128149720
ISBN 10: 0128149728
Pages: 228
Publication Date: 04 December 2020
Audience:
Professional and scholarly
,
Professional & Vocational
Format: Paperback
Publisher's Status: Active
Availability: Manufactured on demand
We will order this item for you from a manufactured on demand supplier.
Author Information
Mei Chen is a principal research manager at Microsoft. She was an associate professor in the Electrical and Computer Engineering Department and director for the Information Science PhD Program at the State University of New York, Albany. She was the founding chair for the Workshop on Computer Vision for Microscopy Image Analysis that has been held in conjunction with the IEEE Conference on Computer Vision and Pattern Recognition since 2016. Mei has published extensively in computer vision and biomedical image analysis. Her work was nominated as a finalist for six Best Paper Awards, for which she won three. She earned a PhD in robotics from the School of Computer Science, Carnegie Mellon University, and an MS and BS from Tsinghua University, Beijing, China.
