scholarly article | Q13442814 |
P818 | arXiv ID | 1807.07701 |
P6179 | Dimensions Publication ID | 1111907384 |
P356 | DOI | 10.1038/S41377-019-0129-Y |
P932 | PMC publication ID | 6363787 |
P698 | PubMed publication ID | 30728961 |
P50 | author | Yibo Zhang | Q89108709 |
Yair Rivenson | Q91106807 | ||
Aydoğan Özcan | Q56230567 | ||
P2093 | author name string | Zhensong Wei | |
Tairan Liu | |||
Kevin de Haan | |||
P2860 | cites work | Deep Learning Enhanced Mobile-Phone Microscopy | Q60501630 |
Wide-field tissue polarimetry allows efficient localized mass spectrometry imaging of biological tissues | Q61901944 | ||
Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning | Q62776217 | ||
Deep learning massively accelerates super-resolution localization microscopy | Q88368591 | ||
Sickle cell disease diagnosis based on spatio-temporal cell dynamics analysis using 3D printed shearing digital holographic microscopy | Q88817449 | ||
Phase recovery and holographic image reconstruction using deep learning in neural networks | Q92159163 | ||
U-Net: Convolutional Networks for Biomedical Image Segmentation | Q104451999 | ||
Deep learning reconstruction of ultrashort pulses | Q105428995 | ||
Propagation phasor approach for holographic image reconstruction | Q27333920 | ||
Deep Learning in Label-free Cell Classification | Q27347513 | ||
A Computational Approach to Edge Detection | Q29029687 | ||
Dual-interference-channel quantitative-phase microscopy of live cell dynamics | Q30497171 | ||
Spatial light interference microscopy (SLIM). | Q33802342 | ||
Lensfree on-chip microscopy over a wide field-of-view using pixel super-resolution | Q33968560 | ||
Wide-field, high-resolution Fourier ptychographic microscopy | Q34212833 | ||
Guidance for laboratories performing molecular pathology for cancer patients | Q34431280 | ||
Assessment of breast pathologies using nonlinear microscopy | Q34442060 | ||
Wide-field computational imaging of pathology slides using lens-free on-chip microscopy | Q35529122 | ||
Tissue refractive index as marker of disease | Q35571561 | ||
Quantitative differential phase contrast imaging in an LED array microscope | Q35630010 | ||
Virtual Hematoxylin and Eosin Transillumination Microscopy Using Epi-Fluorescence Imaging | Q36097343 | ||
Preparation of Formalin-fixed Paraffin-embedded Tissue Cores for both RNA and DNA Extraction | Q36119886 | ||
Automated Detection of P. falciparum Using Machine Learning Algorithms with Quantitative Phase Images of Unstained Cells | Q36135734 | ||
Imaging without lenses: achievements and remaining challenges of wide-field on-chip microscopy | Q36336814 | ||
A survey on deep learning in medical image analysis | Q38646751 | ||
Simultaneous amplitude-contrast and quantitative phase-contrast microscopy by numerical reconstruction of Fresnel off-axis holograms | Q39837882 | ||
Quantitative phase microscopy spatial signatures of cancer cells. | Q40462401 | ||
Holographic deep learning for rapid optical screening of anthrax spores | Q41257374 | ||
Maskless imaging of dense samples using pixel super-resolution based multi-height lensfree on-chip microscopy | Q42091095 | ||
Reflective interferometric chamber for quantitative phase imaging of biological sample dynamics | Q42588055 | ||
High-precision microscopic phase imaging without phase unwrapping for cancer cell identification | Q45393003 | ||
Fast and robust multiframe super resolution | Q46083307 | ||
Edge sparsity criterion for robust holographic autofocusing | Q48534542 | ||
Hilbert phase microscopy for investigating fast dynamics in transparent systems. | Q50764134 | ||
Scattering-phase theorem. | Q51580446 | ||
Rapid intraoperative histology of unprocessed surgical specimens via fibre-laser-based stimulated Raman scattering microscopy | Q57154107 | ||
Extended depth-of-field in holographic imaging using deep-learning-based autofocusing and phase recovery | Q57541040 | ||
Deep learning microscopy | Q57541047 | ||
Deep learning enables cross-modality super-resolution in fluorescence microscopy | Q60501623 | ||
P4510 | describes a project that uses | deep learning | Q197536 |
P433 | issue | 1 | |
P407 | language of work or name | English | Q1860 |
P921 | main subject | deep learning | Q197536 |
P304 | page(s) | 23 | |
P577 | publication date | 2019-02-06 | |
P1433 | published in | Light: Science & Applications | Q29310572 |
P1476 | title | PhaseStain: the digital staining of label-free quantitative phase microscopy images using deep learning | |
P478 | volume | 8 |
Q90912533 | Computational cytometer based on magnetically modulated coherent imaging and deep learning |
Q92936209 | Deep Learning-Based Single-Cell Optical Image Studies |
Q90912490 | Deep learning in holography and coherent imaging |
Q94927825 | Deep learning-enabled point-of-care sensing using multiplexed paper-based sensors |
Q96431533 | DeepSTORM3D: dense 3D localization microscopy and PSF design by deep learning |
Q91791907 | Design of task-specific optical systems using broadband diffractive neural networks |
Q94923503 | Digital synthesis of histological stains using micro-structured and multiplexed virtual staining of label-free tissue |
Q91809929 | Fast stimulated Raman and second harmonic generation imaging for intraoperative gastro-intestinal cancer detection |
Q98205099 | High spatially sensitive quantitative phase imaging assisted with deep neural network for classification of human spermatozoa under stressed condition |
Q102210968 | Integrative quantitative-phase and airy light-sheet imaging |
Q104111159 | Phase imaging with computational specificity (PICS) for measuring dry mass changes in sub-cellular compartments |
Q90663192 | Quantitative Histopathology of Stained Tissues using Color Spatial Light Interference Microscopy (cSLIM) |
Q89773047 | Quantitative scoring of epithelial and mesenchymal qualities of cancer cells using machine learning and quantitative phase imaging |
Q100634298 | SHIFT: speedy histological-to-immunofluorescent translation of a tumor signature enabled by deep learning |
Q103826089 | VISTA: VIsual Semantic Tissue Analysis for pancreatic disease quantification in murine cohorts |
Search more.