DeepAI AI Chat
Log In Sign Up

Increasing a microscope's effective field of view via overlapped imaging and machine learning

by   Xing Yao, et al.

This work demonstrates a multi-lens microscopic imaging system that overlaps multiple independent fields of view on a single sensor for high-efficiency automated specimen analysis. Automatic detection, classification and counting of various morphological features of interest is now a crucial component of both biomedical research and disease diagnosis. While convolutional neural networks (CNNs) have dramatically improved the accuracy of counting cells and sub-cellular features from acquired digital image data, the overall throughput is still typically hindered by the limited space-bandwidth product (SBP) of conventional microscopes. Here, we show both in simulation and experiment that overlapped imaging and co-designed analysis software can achieve accurate detection of diagnostically-relevant features for several applications, including counting of white blood cells and the malaria parasite, leading to multi-fold increase in detection and processing throughput with minimal reduction in accuracy.


page 2

page 4

page 6

page 9


Automated Blood Cell Detection and Counting via Deep Learning for Microfluidic Point-of-Care Medical Devices

Automated in-vitro cell detection and counting have been a key theme for...

A survey on automated detection and classification of acute leukemia and WBCs in microscopic blood cells

Leukemia (blood cancer) is an unusual spread of White Blood Cells or Leu...

Multi-label Detection and Classification of Red Blood Cells in Microscopic Images

Cell detection and cell type classification from biomedical images play ...

A fast semi-automatic method for classification and counting the number and types of blood cells in an image

A novel and fast semi-automatic method for segmentation, locating and co...

Enhanced Center Coding for Cell Detection with Convolutional Neural Networks

Cell imaging and analysis are fundamental to biomedical research because...

A methodology for detection and localization of fruits in apples orchards from aerial images

Computer vision methods based on convolutional neural networks (CNNs) ha...