Results 81 to 90 of about 574 (93)

Drug Resistance Classification of Cancer Cells Based on Digital Holographic Flow Cytometry and Machine Learning

OSA Optical Sensors and Sensing Congress 2021 (AIS, FTS, HISE, SENSORS, ES), 2021
In this work, we use digital holographic (DH) microscope coupled to a label-free and high-throughput microfluidic cytometer to automatically detect the drug resistance of Epithelial Ovarian Cancer (EOC) cells reinforced by machine learning.
Lu Xin, Wen Xiao, Leiping Che, JinJin Liu, Lisa Miccio, Vittorio Bianco, Pasquale Memmolo, Pietro Ferraro, Xiaoping Li, Feng Pan   +9 more
openaire   +1 more source

Growth Characteristic Analysis of Haematococcus pluvialis in a Microfluidic Chip Using Digital in-Line Holographic Flow Cytometry

Analytical Chemistry, 2022
In order to obtain high yield of astaxanthin, a high-value compound with ultrastrong antioxidant capacity, it is necessary to identify the growth characteristics (biomass, morphology, and size) of Haematococcus pluvialis. The current detection methods have the disadvantages of labor-consuming operation or complicated measurement system. It is an urgent
Chaolong Song, Zhe Chen, Xinqi Zheng, Shimin Yang, Xiudong Duan, Yongguang Jiang, Xin Tu, Jinqiang Gan, Shulan Jiang   +8 more
openaire   +2 more sources

Common path off-axis digital holographic flow cytometry based on lateral shearing using beam splitter

Optical Methods for Inspection, Characterization, and Imaging of Biomaterials VII
Rishikesh Kulkarni, Anik Ghosh, Harshal Chaudhari   +2 more
exaly   +2 more sources

Digital holographic flow cytometry for early screening of urothelial carcinoma

Optica Digital Holography and Three-Dimensional Imaging 2024 (DH)
In this work, we use digital holographic (DH) microscope coupled to a label-free and high-throughput flow cytometer for early screening of urothelial carcinoma (UC) cells reinforced by deep learning.
Feng Pan, Lu Xin, Wen Xiao, Hao Wang, Ran Peng, Xi Xiao   +5 more
openaire   +1 more source

Screening for urothelial carcinoma cells in urine based on digital holographic flow cytometry through machine learning and deep learning methods

Lab on a Chip
Digital holographic flow cytometry, aided by machine learning and deep learning algorithms, was employed to screen for urothelial carcinoma cells in urine samples with varying osmotic pressures.
Lu Xin, Xi Xiao, Wen Xiao, Ran Peng, Hao Wang, Feng Pan   +5 more
openaire   +2 more sources

High-throughput and high-precision flow cytometry based on digital holographic microscopy

Optical Methods for Inspection, Characterization, and Imaging of Biomaterials VI, 2023
Feng Pan, Wen Xiao, Lu Xin, Hao Wang, Ran Peng, Xi Xiao   +5 more
openaire   +1 more source

Early detection of urothelial carcinoma allowed by AI-based digital holographic flow cytometry

Optical Methods for Inspection, Characterization, and Imaging of Biomaterials VII
Jie Yang, Xiao Xi, Ran Peng, Feng Pan, Xuemin Li, Ruiping Guo, Luqi Wang, Sara Coppola, Hao Wang   +8 more
openaire   +1 more source

Enhanced Phase Compensation in Digital Holographic Microscopic Imaging Flow Cytometry Using Radial Basis Function Neural Networks

Optics & Laser Technology
Yongan Wen, Yunqi Song, Zixuan Han, Rongke Gao, Feifei Wang, Xiaozhe Chen, Liandong Yu, Yang Lu   +7 more
openaire   +1 more source

Cell Classification in Digital Holographic Flow Cytometry via Direct Hologram Analysis Using Deep Learning

Wen Yongan, Song Yunqi, Chen Xiaozhe, Wang Feifei, Yu Sen, Liu Tao, Jia Huakun, Lu Yang, Yu Liandong   +8 more
openaire   +1 more source

Moving into a new dimension: Tracking migrating cells with digital holographic cytometry in 3D

Cytometry Part A: the Journal of the International Society for Analytical Cytology, 2019
Anette Gjörloff Wingren
exaly