Classification of unlabeled cells using lensless digital holographic images and deep neural networks | Zendy

Duofang Chen | Zendy; Zhaohui Wang | Zendy; Kai Chen | Zendy; Qi Zeng | Zendy; Lin Wang | Zendy; Xinyi Xu | Zendy; Jimin Liang | Zendy; Xueli Chen | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Classification of unlabeled cells using lensless digital holographic images and deep neural networks

Author(s) -

Duofang Chen,

Zhaohui Wang,

Kai Chen,

Qi Zeng,

Lin Wang,

Xinyi Xu,

Jimin Liang,

Xueli Chen

Publication year - 2021

Publication title -

quantitative imaging in medicine and surgery

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.766

H-Index - 21

eISSN - 2223-4292

pISSN - 2223-4306

DOI - 10.21037/qims-21-16

Subject(s) - convolutional neural network , artificial intelligence , computer science , holography , digital holography , computer vision , pattern recognition (psychology) , digital pathology , optics , physics

Image-based cell analytic methodologies offer a relatively simple and economical way to analyze and understand cell heterogeneities and developments. Owing to developments in high-resolution image sensors and high-performance computation processors, the emerging lensless digital holography technique enables a simple and cost-effective approach to obtain label-free cell images with a large field of view and microscopic spatial resolution.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research