Artificial Intelligence Empowerment Upgrade of Traditional Optical Microscopy
Based on Portable Computing Device
SHANG Shang1
, LIN Sijie2a, GUO Weixin2b, CONG Fengyu1
1. School of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology,
Dalian Liaoning 116024, China; 2. a. Key Laboratory of Yangtze River Water Environment, Ministry of Education, Department of
Environmental Science, College of Environmental Science and Engineering; b. College of Electronics and Information Engineering,
Tongji University, Shanghai 200092, China
Abstract:Optical microscopes are widely used in biomedical research and clinical medicine. In recent years, deep learning
technology has provided advanced algorithm support for the automatic analysis of microscopic images. However, most of the
microscopes currently installed in Chinese hospitals and scientific research institutions do not have their own deep neural network
image analysis function, and the upgrade of equipment and software requires high costs. This research used portable computing
devices to upgrade traditional digital optical microscopes with artificial intelligence, and used Jetson TX2 portable devices to run
Faster R-CNN network to achieve three-frame rate classification and detection efficiency for zebrafish eggs. The detection sensitivity
was higher than 0.88, the specificity is higher than 0.94, and the portable device used was small and could be conveniently placed
next to the microscope. This research provides a convenient, inexpensive and popular technical solution for artificial intelligence to
empower traditional microscopes.
尚尚1
,林思劼2a,郭伟新2b,丛丰裕1. 基于便携式计算设备的传统光学显微镜的AI赋能升级[J]. 中国医疗设备, 2020, 35(8): 16-20.
SHANG Shang1
, LIN Sijie2a, GUO Weixin2b, CONG Fengyu1. Artificial Intelligence Empowerment Upgrade of Traditional Optical Microscopy
Based on Portable Computing Device. China Medical Devices, 2020, 35(8): 16-20.