IMACEL: A cloud-based bioimage analysis platform for morphological analysis and image classification

Automated quantitative image analysis is essential for all fields of life science research. Although several software programs and algorithms have been developed for bioimage processing, an advanced knowledge of image processing techniques and high-performance computing resources are required to use...

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Bibliographic Details
Published in:PloS one 2019-02, Vol.14 (2), p.e0212619-e0212619
Main Authors: Shimahara, Yuki, Sugawara, Ko, Kojo, Kei H, Kawai, Hiroki, Yoshida, Yuya, Hasezawa, Seiichiro, Kutsuna, Natsumaro
Format: Article
Language:English
Subjects:
Active learning
Algorithms
Analysis
Artificial intelligence
Automation
Biology
Biology and Life Sciences
Cancer
Cell cycle
Classification
Cloud Computing
Computer and Information Sciences
Data mining
Engineering and Technology
Image analysis
Image classification
Image processing
Image processing software
Image Processing, Computer-Assisted
Learning algorithms
Life sciences
Life sciences research
Machine Learning
Medicine and Health Sciences
Morphology
Quantitative analysis
R&D
Research & development
Research and Analysis Methods
Researchers
Social science research
Software
Virtual environments
Virtual machines
Web browsers
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Summary:Automated quantitative image analysis is essential for all fields of life science research. Although several software programs and algorithms have been developed for bioimage processing, an advanced knowledge of image processing techniques and high-performance computing resources are required to use them. Hence, we developed a cloud-based image analysis platform called IMACEL, which comprises morphological analysis and machine learning-based image classification. The unique click-based user interface of IMACEL's morphological analysis platform enables researchers with limited resources to evaluate particles rapidly and quantitatively without prior knowledge of image processing. Because all the image processing and machine learning algorithms are performed on high-performance virtual machines, users can access the same analytical environment from anywhere. A validation study of the morphological analysis and image classification of IMACEL was performed. The results indicate that this platform is an accessible and potentially powerful tool for the quantitative evaluation of bioimages that will lower the barriers to life science research.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0212619