Machine Learning Based Single-Frame Super-Resolution Processing for Lensless Blood Cell Counting

Machine Learning Based Single-Frame Super-Resolution Processing for Lensless Blood Cell Counting

A lensless blood cell counting system integrating microfluidic channel and a complementary metal oxide semiconductor (CMOS) image sensor is a promising technique to miniaturize the conventional optical lens based imaging system for point-of-care testing (POCT). However, such a system has limited res...

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Bibliographic Details
Main Authors: Xiwei Huang, Yu Jiang, Xu Liu, Hang Xu, Zhi Han, Hailong Rong, Haiping Yang, Mei Yan, Hao Yu
Format: Article
Language:English
Published: MDPI AG 2016-11-01
Series:Sensors
Subjects:
microfluidic cytometer
super-resolution
convolutional neural network
extreme learning machine
CMOS image sensor
point-of-care testing
Online Access:http://www.mdpi.com/1424-8220/16/11/1836

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http://www.mdpi.com/1424-8220/16/11/1836

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