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3D convolutional neural networks predict cellular metabolic pathway use from fluorescence lifetime decay data

APL bioengineering, 2024-03, Vol.8 (1), p.016112-016112-12

2024

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Perfusability and immunogenicity of implantable pre-vascularized tissues recapitulating features of native capillary network

Bioactive materials, 2023-12, Vol.30, p.184-199

2023

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Label-free spatially maintained measurements of metabolic phenotypes in cells

Frontiers in bioengineering and biotechnology, 2023-11, Vol.11, p.1293268-1293268

2023

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Comparison of phasor analysis and biexponential decay curve fitting of autofluorescence lifetime imaging data for machine learning prediction of cellular phenotypes

Frontiers in bioinformatics, 2023-06, Vol.3, p.1210157-1210157

2023

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Evaluation of Cellpose segmentation with sequential thresholding for instance segmentation of cytoplasms within autofluorescence images

Computers in biology and medicine, 2024-09, Vol.179, p.108846, Article 108846

2024

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Mutant KRAS Exosomes Alter the Metabolic State of Recipient Colonic Epithelial Cells

Cellular and molecular gastroenterology and hepatology, 2018-01, Vol.5 (4), p.627-629.e6

2018

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Identification of rare cell populations in autofluorescence lifetime image data

Cytometry. Part A, 2022-06, Vol.101 (6), p.497-506

2022

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Fluorescence intensity and lifetime redox ratios detect metabolic perturbations in T cells

Biomedical optics express, 2020-10, Vol.11 (10), p.5674-5688

2020

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Optical metabolic imaging quantifies heterogeneous cell populations

Biomedical optics express, 2015-02, Vol.6 (2), p.559-573

2015

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Decellularized organ biomatrices facilitate quantifiable in vitro 3D cancer metastasis models

Soft matter, 2022-08, Vol.18 (31), p.5791-5806

2022

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Classifying T cell activity in autofluorescence intensity images with convolutional neural networks

Journal of biophotonics, 2020-03, Vol.13 (3), p.e201960050-n/a

2020

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Label-free optical imaging of cell function and collagen structure for cell-based therapies

Current opinion in biomedical engineering, 2023-03, Vol.25, p.100433, Article 100433

2023

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Temporal binning of time-correlated single photon counting data improves exponential decay fits and imaging speed

Biomedical optics express, 2016-04, Vol.7 (4), p.1385-1399

2016

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Author Correction: Drug response in organoids generated from frozen primary tumor tissues

Scientific reports, 2019-04, Vol.9 (1), p.6517-6517, Article 6517

2019

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In vivo hyperspectral imaging of microvessel response to trastuzumab treatment in breast cancer xenografts

Biomedical optics express, 2014-07, Vol.5 (7), p.2247-2261

2014

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Abstract 4241: Predicting clinical response in breast cancer using cellular-resolution optical metabolic imaging

Cancer research (Chicago, Ill.), 2016-07, Vol.76 (14_Supplement), p.4241-4241

2016

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Action potential block in neurons by infrared light

Neurophotonics (Print), 2016-10, Vol.3 (4), p.040501-040501

2016

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150 Mutant KRAS-Dependent Changes in Exosomes and Recipient Cell Metabolism

Gastroenterology (New York, N.Y. 1943), 2013-05, Vol.144 (5), p.S-34-S-34

2013

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Design and Implementation of Privilege for Sale, a JEDI Activity for a Biomedical Engineering Introductory Course

Biomedical engineering education, 2022-09, Vol.2 (2), p.183-188

2022

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Volumetric imaging of human mesenchymal stem cells

PloS one, 2023-03, Vol.18 (3), p.e0282298

2023

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Autofluorescence Imaging to Evaluate Cellular Metabolism

Journal of visualized experiments, 2021-11 (177)

2021

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Autofluorescence Imaging of T cell Activation

The Journal of immunology (1950), 2018-05, Vol.200 (1_Supplement), p.120-120.13

2018

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Abstract P3-06-38: Optical metabolic imaging predicts therapeutic response in breast cancer tumors and organoids

Cancer research (Chicago, Ill.), 2015-05, Vol.75 (9_Supplement), p.P3-P3-06-38

2015

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A Single Camera Optical System for the Measurement of Helicopter Blade Track and Elastic Deflection

Palmer-Walsh, Alex J

2020

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Optical Metabolic Imaging Identifies Tumor Cell-Cycle Status on a Single-Cell Level

Journal of biophotonics, 2017-05, Vol.11 (1)

2017

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3D convolutional neural networks predict cellular metabolic pathway use from fluorescence lifetime decay data

Perfusability and immunogenicity of implantable pre-vascularized tissues recapitulating features of native capillary network

Label-free spatially maintained measurements of metabolic phenotypes in cells

Comparison of phasor analysis and biexponential decay curve fitting of autofluorescence lifetime imaging data for machine learning prediction of cellular phenotypes

Evaluation of Cellpose segmentation with sequential thresholding for instance segmentation of cytoplasms within autofluorescence images

Mutant KRAS Exosomes Alter the Metabolic State of Recipient Colonic Epithelial Cells

Identification of rare cell populations in autofluorescence lifetime image data

Fluorescence intensity and lifetime redox ratios detect metabolic perturbations in T cells

Optical metabolic imaging quantifies heterogeneous cell populations

Decellularized organ biomatrices facilitate quantifiable in vitro 3D cancer metastasis models

Classifying T cell activity in autofluorescence intensity images with convolutional neural networks

Label-free optical imaging of cell function and collagen structure for cell-based therapies

Temporal binning of time-correlated single photon counting data improves exponential decay fits and imaging speed

Author Correction: Drug response in organoids generated from frozen primary tumor tissues

In vivo hyperspectral imaging of microvessel response to trastuzumab treatment in breast cancer xenografts

Abstract 4241: Predicting clinical response in breast cancer using cellular-resolution optical metabolic imaging

Action potential block in neurons by infrared light

150 Mutant KRAS-Dependent Changes in Exosomes and Recipient Cell Metabolism

Design and Implementation of Privilege for Sale, a JEDI Activity for a Biomedical Engineering Introductory Course

Volumetric imaging of human mesenchymal stem cells

Autofluorescence Imaging to Evaluate Cellular Metabolism

Autofluorescence Imaging of T cell Activation

Abstract P3-06-38: Optical metabolic imaging predicts therapeutic response in breast cancer tumors and organoids

A Single Camera Optical System for the Measurement of Helicopter Blade Track and Elastic Deflection

Optical Metabolic Imaging Identifies Tumor Cell-Cycle Status on a Single-Cell Level

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