arrow
Return

Multidirectional Image Sensing for Microscopy Based on a Rotatable Robot

delete2015-12-15
delete16
delete
OA
AI
申亚京 (Yajing Shen) *
W
Wenfeng Wan
张立军 (Lijun Zhang)
Y
Yong Li
H
Haojian Lu
W
Weili Ding
DOI:10.3390/s151229872delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
Image sensing at a small scale is essentially important in many fields, including microsample observation, defect inspection, material characterization and so on. However, nowadays, multi-directional micro object imaging is still very challenging due to the limited field of view (FOV) of microscopes. This paper reports a novel approach for multi-directional image sensing in microscopes by developing a rotatable robot. First, a robot with endless rotation ability is designed and integrated with the microscope. Then, the micro object is aligned to the rotation axis of the robot automatically based on the proposed forward-backward alignment strategy. After that, multi-directional images of the sample can be obtained by rotating the robot within one revolution under the microscope. To demonstrate the versatility of this approach, we view various types of micro samples from multiple directions in both optical microscopy and scanning electron microscopy, and panoramic images of the samples are processed as well. The proposed method paves a new way for the microscopy image sensing, and we believe it could have significant impact in many fields, especially for sample detection, manipulation and characterization at a small scale.
Keywords:
multidirectional imaging
robot
microscopy image sensing
micromanipulation
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Sensors cover
Sensors
IF:
3.5
Papers:
7.1W
Citations:
20.9W

Organization

C
City University of Hong Kong
Scholars:
2.3W
Papers: 3.0W
Citations: 6.1W
C
china university of petroleum
Scholars:
4.1W
Papers: 2.7W
Citations: 30