[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Mahjoubfar et al., 2017 - Google Patents

Time Stretch Quantitative Phase Imaging

Mahjoubfar et al., 2017

Document ID
9510486828683697372
Author
Mahjoubfar A
Chen C
Jalali B
Mahjoubfar A
Chen C
Jalali B
Publication year
Publication venue
Artificial Intelligence in Label-free Microscopy: Biological Cell Classification by Time Stretch

External Links

Snippet

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single …
Continue reading at link.springer.com (other versions)

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/62Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
    • G01N21/63Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
    • G01N21/65Raman scattering
    • G01N2021/653Coherent methods [CARS]
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/62Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
    • G01N21/63Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
    • G01N21/64Fluorescence; Phosphorescence
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00Investigating characteristics of particles; Investigating permeability, pore-volume, or surface-area of porous materials
    • G01N15/10Investigating individual particles
    • G01N15/14Electro-optical investigation, e.g. flow cytometers
    • G01N15/1456Electro-optical investigation, e.g. flow cytometers without spatial resolution of the texture or inner structure of the particle, e.g. processing of pulse signals
    • G01N15/1459Electro-optical investigation, e.g. flow cytometers without spatial resolution of the texture or inner structure of the particle, e.g. processing of pulse signals the analysis being performed on a sample stream
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/17Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/47Scattering, i.e. diffuse reflection
    • G01N21/49Scattering, i.e. diffuse reflection within a body or fluid
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by the preceding groups
    • G01N33/48Investigating or analysing materials by specific methods not covered by the preceding groups biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/5005Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/17Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/35Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infra-red light
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00127Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01JMEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRA-RED, VISIBLE OR ULTRA-VIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00Spectrometry; Spectrophotometry; Monochromators; Measuring colour
    • G01J3/28Investigating the spectrum

Similar Documents

Publication Publication Date Title
Chen et al. Deep learning in label-free cell classification
US10593039B2 (en) Deep learning in label-free cell classification and machine vision extraction of particles
Li et al. Deep cytometry: deep learning with real-time inference in cell sorting and flow cytometry
Nissim et al. Real‐time stain‐free classification of cancer cells and blood cells using interferometric phase microscopy and machine learning
Lei et al. High-throughput imaging flow cytometry by optofluidic time-stretch microscopy
Schnell et al. All-digital histopathology by infrared-optical hybrid microscopy
Clemens et al. Vibrational spectroscopic methods for cytology and cellular research
Hejna et al. High accuracy label-free classification of single-cell kinetic states from holographic cytometry of human melanoma cells
Pilling et al. Quantum cascade laser spectral histopathology: breast cancer diagnostics using high throughput chemical imaging
US9903804B2 (en) Real-time label-free high-throughput cell screening in flow
Lee et al. Multi‐ATOM: Ultrahigh‐throughput single‐cell quantitative phase imaging with subcellular resolution
Mahjoubfar et al. Artificial Intelligence in Label-free Microscopy
Ayyappan et al. Identification and staging of B-cell acute lymphoblastic leukemia using quantitative phase imaging and machine learning
US11530434B2 (en) Cell mass evaluation method and device for analyzing state of cell mass
Poola et al. Label-free nanoscale characterization of red blood cell structure and dynamics using single-shot transport of intensity equation
Woolford et al. Towards automated cancer screening: label‐free classification of fixed cell samples using wavelength modulated Raman spectroscopy
Butola et al. Multimodal on-chip nanoscopy and quantitative phase imaging reveals the nanoscale morphology of liver sinusoidal endothelial cells
Mayerich et al. Breast histopathology using random decision forests-based classification of infrared spectroscopic imaging data
US12147022B2 (en) Dark-field mid-infrared photothermal microscopy
Yip et al. Multimodal FACED imaging for large-scale single-cell morphological profiling
Mann et al. White light phase shifting interferometric microscopy with whole slide imaging for quantitative analysis of biological samples
Taieb et al. Classification of tissue biopsies by Raman spectroscopy guided by quantitative phase imaging and its application to bladder cancer
Mittal et al. A four class model for digital breast histopathology using high-definition Fourier transform infrared (FT-IR) spectroscopic imaging
Li et al. All-optical Fourier-domain-compressed time-stretch imaging with low-pass filtering
Reble et al. Evaluation of Raman spectroscopic macro raster scans of native cervical cone biopsies using histopathological mapping