These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

138 related articles for article (PubMed ID: 38264771)

  • 1. Label-free cell classification in holographic flow cytometry through an unbiased learning strategy.
    Ciaparrone G; Pirone D; Fiore P; Xin L; Xiao W; Li X; Bardozzo F; Bianco V; Miccio L; Pan F; Memmolo P; Tagliaferri R; Ferraro P
    Lab Chip; 2024 Feb; 24(4):924-932. PubMed ID: 38264771
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Speeding up reconstruction of 3D tomograms in holographic flow cytometry
    Pirone D; Sirico D; Miccio L; Bianco V; Mugnano M; Ferraro P; Memmolo P
    Lab Chip; 2022 Feb; 22(4):793-804. PubMed ID: 35076055
    [TBL] [Abstract][Full Text] [Related]  

  • 3. TOP-GAN: Stain-free cancer cell classification using deep learning with a small training set.
    Rubin M; Stein O; Turko NA; Nygate Y; Roitshtain D; Karako L; Barnea I; Giryes R; Shaked NT
    Med Image Anal; 2019 Oct; 57():176-185. PubMed ID: 31325721
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A practical criterion for focusing of unstained cell samples using a digital holographic microscope.
    Malik R; Sharma P; Poulose S; Ahlawat S; Khare K
    J Microsc; 2020 Aug; 279(2):114-122. PubMed ID: 32441768
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Plankton classification with high-throughput submersible holographic microscopy and transfer learning.
    MacNeil L; Missan S; Luo J; Trappenberg T; LaRoche J
    BMC Ecol Evol; 2021 Jun; 21(1):123. PubMed ID: 34134620
    [TBL] [Abstract][Full Text] [Related]  

  • 6. On-chip label-free cell classification based directly on off-axis holograms and spatial-frequency-invariant deep learning.
    Dudaie M; Barnea I; Nissim N; Shaked NT
    Sci Rep; 2023 Jul; 13(1):12370. PubMed ID: 37524884
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Screening for urothelial carcinoma cells in urine based on digital holographic flow cytometry through machine learning and deep learning methods.
    Xin L; Xiao X; Xiao W; Peng R; Wang H; Pan F
    Lab Chip; 2024 May; 24(10):2736-2746. PubMed ID: 38660758
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Accurate label-free 3-part leukocyte recognition with single cell lens-free imaging flow cytometry.
    Li Y; Cornelis B; Dusa A; Vanmeerbeeck G; Vercruysse D; Sohn E; Blaszkiewicz K; Prodanov D; Schelkens P; Lagae L
    Comput Biol Med; 2018 May; 96():147-156. PubMed ID: 29573668
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Label-free, high-throughput holographic screening and enumeration of tumor cells in blood.
    Singh DK; Ahrens CC; Li W; Vanapalli SA
    Lab Chip; 2017 Aug; 17(17):2920-2932. PubMed ID: 28718848
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Deep Cytometry: Deep learning with Real-time Inference in Cell Sorting and Flow Cytometry.
    Li Y; Mahjoubfar A; Chen CL; Niazi KR; Pei L; Jalali B
    Sci Rep; 2019 Jul; 9(1):11088. PubMed ID: 31366998
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Label-free high temporal resolution assessment of cell proliferation using digital holographic microscopy.
    Janicke B; Kårsnäs A; Egelberg P; Alm K
    Cytometry A; 2017 May; 91(5):460-469. PubMed ID: 28437571
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Automated classification of cell morphology by coherence-controlled holographic microscopy.
    Strbkova L; Zicha D; Vesely P; Chmelik R
    J Biomed Opt; 2017 Aug; 22(8):1-9. PubMed ID: 28836416
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Quantitative phase imaging of cells in a flow cytometry arrangement utilizing Michelson interferometer-based off-axis digital holographic microscopy.
    Min J; Yao B; Trendafilova V; Ketelhut S; Kastl L; Greve B; Kemper B
    J Biophotonics; 2019 Sep; 12(9):e201900085. PubMed ID: 31169960
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Automatic phase aberration compensation for digital holographic microscopy based on deep learning background detection.
    Nguyen T; Bui V; Lam V; Raub CB; Chang LC; Nehmetallah G
    Opt Express; 2017 Jun; 25(13):15043-15057. PubMed ID: 28788938
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Holographic virtual staining of individual biological cells.
    Nygate YN; Levi M; Mirsky SK; Turko NA; Rubin M; Barnea I; Dardikman-Yoffe G; Haifler M; Shalev A; Shaked NT
    Proc Natl Acad Sci U S A; 2020 Apr; 117(17):9223-9231. PubMed ID: 32284403
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Three-dimensional quantitative phase imaging of blood coagulation structures by optical projection tomography in flow cytometry using digital holographic microscopy.
    Funamizu H; Aizu Y
    J Biomed Opt; 2018 Oct; 24(3):1-6. PubMed ID: 30302967
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Robust Phase Unwrapping via Deep Image Prior for Quantitative Phase Imaging.
    Yang F; Pham TA; Brandenberg N; Lutolf MP; Ma J; Unser M
    IEEE Trans Image Process; 2021; 30():7025-7037. PubMed ID: 34329165
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Single Cell Analysis of Stored Red Blood Cells Using Ultra-High Throughput Holographic Cytometry.
    Park HS; Price H; Ceballos S; Chi JT; Wax A
    Cells; 2021 Sep; 10(9):. PubMed ID: 34572104
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Quantitative phase microscopy spatial signatures of cancer cells.
    Roitshtain D; Wolbromsky L; Bal E; Greenspan H; Satterwhite LL; Shaked NT
    Cytometry A; 2017 May; 91(5):482-493. PubMed ID: 28426133
    [TBL] [Abstract][Full Text] [Related]  

  • 20. AMC-Net: Asymmetric and multi-scale convolutional neural network for multi-label HPA classification.
    Xiang S; Liang Q; Hu Y; Tang P; Coppola G; Zhang D; Sun W
    Comput Methods Programs Biomed; 2019 Sep; 178():275-287. PubMed ID: 31416555
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.