Imaging flow cytometry has been widely adopted in numerous applications such as optical
sensing, environmental monitoring, clinical diagnostics, and precision agriculture. The …

Imaging flow cytometry (IFC) captures multichannel images of hundreds of thousands of
single cells within minutes. IFC is seeing a paradigm shift from low-to high-information …

Imaging flow cytometry combines the high-event-rate nature of flow cytometry with the
advantages of single-cell image acquisition associated with microscopy. The measurement …

Deep learning is an idea technique for image classification. Imaging flow cytometer enables
high throughput cell image acquisition and some have integrated with real-time cell sorting …

Imaging flow cytometry (IFC) enables the high throughput collection of morphological and
spatial information from hundreds of thousands of single cells. This high content, information …

A new label‐free imaging flow cytometry method for noninvasive and automated biological
cell classification is presented. Each cell is rolled during flow, and its off‐axis holograms …

In this review, we focus on the applications of machine learning methods for analyzing
image data acquired in imaging flow cytometry technologies. We propose that the analysis …

Recent development of imaging flow cytometry (IFC) has enabled the measurements of
single cells with high throughput, where fluorescent labels provide specificity for cellular …

Image-based flow cytometry combines the throughput of traditional flow cytometry with the
ability to visually confirm findings and collect novel data that would not be possible …

Imaging flow cytometry (IFC) is an emerging technology that acquires single-cell images at
high-throughput for analysis of a cell population. Rich information that comes from high …