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| http://dx.doi.org/10.1364/OPN.21.12.000027 | DOI Listing |
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Label-free detection and simultaneous viability determination of CTCs by lens-free imaging cytometry.
Anal Bioanal Chem
January 2025
Department of Gastroenterology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450001, China.
Article Synopsis
- The study focuses on detecting rare circulating tumor cells (CTCs) in blood, which is crucial for cancer diagnosis and treatment monitoring.
- A lens-free imaging system was developed that allows for high-resolution imaging and faster detection of CTCs, achieving a throughput of 150,000 cells per minute.
- Results showed high accuracy in identifying live and dead CTCs in cancer patients, with significant findings indicating CTC death occurs rapidly after leaving the body, thus proving the method's effectiveness compared to traditional techniques.
Deep Learning Enabled Universal Multiplexed Fluorescence Detection for Point-of-Care Applications.
ACS Sens
August 2024
Department of Electrical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, United States.
There is a significant demand for multiplexed fluorescence sensing and detection across a range of applications. Yet, the development of portable and compact multiplexable systems remains a substantial challenge. This difficulty largely stems from the inherent need for spectrum separation, which typically requires sophisticated and expensive optical components.
View Article and Find Full Text PDFLabel-Free CD34+ Cell Identification Using Deep Learning and Lens-Free Shadow Imaging Technology.
Biosensors (Basel)
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Department of Electronics and Information Engineering, Korea University, Sejong 30019, Republic of Korea.
Accurate and efficient classification and quantification of CD34+ cells are essential for the diagnosis and monitoring of leukemia. Current methods, such as flow cytometry, are complex, time-consuming, and require specialized expertise and equipment. This study proposes a novel approach for the label-free identification of CD34+ cells using a deep learning model and lens-free shadow imaging technology (LSIT).
View Article and Find Full Text PDFMicroscopic Imaging Methods for Organ-on-a-Chip Platforms.
Micromachines (Basel)
February 2022
Department of Biomedical Engineering, The University of Arizona, Tucson, AZ 85721, USA.
Microscopic imaging is essential and the most popular method for in situ monitoring and evaluating the outcome of various organ-on-a-chip (OOC) platforms, including the number and morphology of mammalian cells, gene expression, protein secretions, etc. This review presents an overview of how various imaging methods can be used to image organ-on-a-chip platforms, including transillumination imaging (including brightfield, phase-contrast, and holographic optofluidic imaging), fluorescence imaging (including confocal fluorescence and light-sheet fluorescence imaging), and smartphone-based imaging (including microscope attachment-based, quantitative phase, and lens-free imaging). While various microscopic imaging methods have been demonstrated for conventional microfluidic devices, a relatively small number of microscopic imaging methods have been demonstrated for OOC platforms.
View Article and Find Full Text PDFGenerative optical modeling of whole blood for detecting platelets in lens-free images.
Biomed Opt Express
April 2020
Johns Hopkins University, Baltimore, MD 21218, USA.
In this paper, we consider the task of detecting platelets in images of diluted whole blood taken with a lens-free microscope. Despite having several advantages over traditional microscopes, lens-free imaging systems have the significant challenge that the resolution of the system is typically limited by the pixel dimensions of the image sensor. As a result of this limited resolution, detecting platelets is very difficult even by manual inspection of the images due to the fact that platelets occupy just a few pixels of the reconstructed image.
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