AI on a chip
Artificial intelligence (AI) has dramatically changed the landscape of science, industry,
defence, and medicine in the last several years. Supported by considerably enhanced …
defence, and medicine in the last several years. Supported by considerably enhanced …
Computer vision meets microfluidics: a label-free method for high-throughput cell analysis
S Zhou, B Chen, ES Fu, H Yan - Microsystems & Nanoengineering, 2023 - nature.com
In this paper, we review the integration of microfluidic chips and computer vision, which has
great potential to advance research in the life sciences and biology, particularly in the …
great potential to advance research in the life sciences and biology, particularly in the …
Deep imaging flow cytometry
Imaging flow cytometry (IFC) has become a powerful tool for diverse biomedical applications
by virtue of its ability to image single cells in a high-throughput manner. However, there …
by virtue of its ability to image single cells in a high-throughput manner. However, there …
Toward deep biophysical cytometry: prospects and challenges
The biophysical properties of cells reflect their identities, underpin their homeostatic state in
health, and define the pathogenesis of disease. Recent leapfrogging advances in …
health, and define the pathogenesis of disease. Recent leapfrogging advances in …
Optofluidic imaging meets deep learning: from merging to emerging
Propelled by the striking advances in optical microscopy and deep learning (DL), the role of
imaging in lab-on-a-chip has dramatically been transformed from a silo inspection tool to a …
imaging in lab-on-a-chip has dramatically been transformed from a silo inspection tool to a …
Virtual-freezing fluorescence imaging flow cytometry with 5-aminolevulinic acid stimulation and antibody labeling for detecting all forms of circulating tumor cells
Circulating tumor cells (CTCs) are precursors to cancer metastasis. In blood circulation, they
take various forms such as single CTCs, CTC clusters, and CTC–leukocyte clusters, all of …
take various forms such as single CTCs, CTC clusters, and CTC–leukocyte clusters, all of …
Interpretable unsupervised learning enables accurate clustering with high-throughput imaging flow cytometry
A primary challenge of high-throughput imaging flow cytometry (IFC) is to analyze the vast
amount of imaging data, especially in applications where ground truth labels are …
amount of imaging data, especially in applications where ground truth labels are …
Low-latency label-free image-activated cell sorting using fast deep learning and AI inferencing
R Tang, L Xia, B Gutierrez, I Gagne, A Munoz… - Biosensors and …, 2023 - Elsevier
Classification and sorting of cells using image-activated cell sorting (IACS) systems can
bring significant insight to biomedical sciences. Incorporating deep learning algorithms into …
bring significant insight to biomedical sciences. Incorporating deep learning algorithms into …
A high-throughput technique to map cell images to cell positions using a 3D imaging flow cytometer
We develop a high-throughput technique to relate positions of individual cells to their three-
dimensional (3D) imaging features with single-cell resolution. The technique is particularly …
dimensional (3D) imaging features with single-cell resolution. The technique is particularly …
Accessible high-speed image-activated cell sorting
Over the past six decades, fluorescence-activated cell sorting (FACS) has become an
essential technology for basic and clinical research by enabling the isolation of cells of …
essential technology for basic and clinical research by enabling the isolation of cells of …