ArticlePloS one2013
Real time blood testing using quantitative phase imaging.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
26 citing papers in PubMed.
- Halo-free quantitative phase imaging via physics-constrained self-supervised network.Journal of biomedical optics · 2026Article
- Real-time processing of high-throughput quantitative phase microscopy data using a Jetson Orin Nano.Biophotonics discovery · 2026Article
- Digital Holographic Microscopy in Veterinary Medicine-A Feasibility Study to Analyze Label-Free Leukocytes in Blood and Milk of Dairy Cows.Animals : an open access journal from MDPI · 2024Article
- Changes to the shape, orientation and packing of red cells as a function of retinal capillary size.Biomedical optics express · 2024Article
- Quantitative Measurements of Red Blood Cell Indices Using Spectroscopic Differential Phase-Contrast Microscopy.Chemical & biomedical imaging · 2023Article
- Review
- Morphological Characteristics, Hemoglobin Content, and Membrane Mechanical Properties of Red Blood Cell Delivery Systems.ACS applied materials & interfaces · 2022Article
- A Light-Sheet-Based Imaaging Spectrometer to Characterize Acridine Orange Fluorescence within Leukocytes.Diagnostics (Basel, Switzerland) · 2020Article
- Simple adaptive mobile phone screen illumination for dual phone differential phase contrast (DPDPC) microscopy.Biomedical optics express · 2019Article
- Deep Cytometry: Deep learning with Real-time Inference in Cell Sorting and Flow Cytometry.Scientific reports · 2019Article
- Invited Article: Digital refocusing in quantitative phase imaging for flowing red blood cells.APL photonics · 2018Article
- 3D surface morphology imaging of opaque microstructures via light-field microscopy.Scientific reports · 2018Article
- Automated Cell Segmentation for Quantitative Phase Microscopy.IEEE transactions on medical imaging · 2018Article
- A Time-lapse, Label-free, Quantitative Phase Imaging Study of Dormant and Active Human Cancer Cells.Journal of visualized experiments : JoVE · 2018Article
- Real-time halo correction in phase contrast imaging.Biomedical optics express · 2018Article
- A new red cell index and portable RBC analyzer for screening of iron deficiency and Thalassemia minor in a Chinese population.Scientific reports · 2017Article
- Melittin-induced alterations in morphology and deformability of human red blood cells using quantitative phase imaging techniques.Scientific reports · 2017Article
- Large population cell characterization using quantitative phase cytometer.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2017Article
- Refractive index tomograms and dynamic membrane fluctuations of red blood cells from patients with diabetes mellitus.Scientific reports · 2017Article
- Tomographic flow cytometry by digital holography.Light, science & applications · 2017Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
We demonstrate a real-time blood testing system that can provide remote diagnosis with minimal human intervention in economically challenged areas. Our instrument combines novel advances in label-free optical imaging with parallel computing. Specifically, we use quantitative phase imaging for extracting red blood cell morphology with nanoscale sensitivity and NVIDIA's CUDA programming language to perform real time cellular-level analysis. While the blood smear is translated through focus, our system is able to segment and analyze all the cells in the one megapixel field of view, at a rate of 40 frames/s. The variety of diagnostic parameters measured from each cell (e.g., surface area, sphericity, and minimum cylindrical diameter) are currently not available with current state of the art clinical instruments. In addition, we show that our instrument correctly recovers the red blood cell volume distribution, as evidenced by the excellent agreement with the cell counter results obtained on normal patients and those with microcytic and macrocytic anemia. The final data outputted by our instrument represent arrays of numbers associated with these morphological parameters and not images. Thus, the memory necessary to store these data is of the order of kilobytes, which allows for their remote transmission via, for example, the cellular network. We envision that such a system will dramatically increase access for blood testing and furthermore, may pave the way to digital hematology.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.