Kyle P. Quinn
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Assistant Professor
Also affiliated: Tufts University (2011–2026); Brigham and Women's Hospital (2014); Harvard University (2014); California University of Pennsylvania (2007–2008); In-Q-Tel (2016); AVEO Oncology (United States) (2013); Cambridge Systematics (United States) (2013); Bioengineering Center (2009–2010); University of Virginia (2025); University of Pennsylvania (2006–2011); Philadelphia University (2010)
Faculty Researcher
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Kyle P. Quinn's research focuses on developing and applying advanced optical imaging techniques, particularly multiphoton microscopy, for biological and medical applications. He investigates the label-free characterization of cellular and tissue structures to understand disease progression and healing processes. His work includes the development of deep learning algorithms for automated image analysis, enhancing the segmentation and extraction of biomarkers from microscopy data.
Quinn has received federal funding to support his investigations into automated wound analysis using deep learning and to characterize aged skin for predicting delayed wound healing. He also leads an I-Corps project focused on a skin autofluorescence imager for rapid wound assessment. His research group collaborates with other investigators at the University of Arkansas at Fayetteville, including Alan E. Woessner, Jake D. Jones, Jin-Woo Kim, and Patrick Kuczwara, on projects involving collagen microstructure, stem cell behavior, and disease monitoring.
His publication record demonstrates a breadth of study, including work on collagen in skin and valve tissues, metabolic imaging in cells, and the use of microscopy in detecting conditions like calcific aortic valve disease. Quinn's scholarship metrics indicate a significant research output, with an h-index of 36, 175 total publications, and over 4,300 citations.
Metrics
- h-index: 36
- Publications: 177
- Citations: 4,411
Selected Publications
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Force-responsive biomaterials drive tissue repair by harnessing endogenous growth factors (2026)
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Autofluorescence lifetime of gelatin-methacrylate hydrogels is sensitive to changes in crosslinking and post-gelation pH (2026)
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Optical metabolic imaging of tumor recurrence in non-small cell lung cancer (2026)
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<i>In Vivo</i> , Label-Free Multiphoton Microscopy Is Sensitive to Altered Metabolism and Structure in Aged Skin (2026)
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Metabolic Imaging and Characterization of Multicomponent Spheroid Models in Vitro. (2025)
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Consensus guidelines for cellular label-free optical metabolic imaging: ensuring accuracy and reproducibility in metabolic profiling (2025)
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Understanding Skin Wound Healing Dynamics Through AI-Powered Analysis of Label-free Multiphoton Imaging (2025)
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Optical imaging of treatment-naïve human NSCLC reveals changes associated with metastatic recurrence (2024)
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A three-dimensional valve-on-chip microphysiological system implicates cell cycle progression, cholesterol metabolism and protein homeostasis in early calcific aortic valve disease progression (2024)
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Identifying and training deep learning neural networks on biomedical-related datasets (2024)
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Quantifying the Interaction between Age and Diabetes on Skin Wound Metabolism Using In Vivo Multiphoton Microscopy (2024)
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Quantification of age-related changes in the structure and mechanical function of skin with multiscale imaging (2024)
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Pre-Incisional and Multiple Intradermal Injection of N-Acetylcysteine Slightly Improves Incisional Wound Healing in an Animal Model (2024)
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CapsNet for medical image segmentation (2024)
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Mechanical Models of Collagen Networks for Understanding Changes in the Failure Properties of Aging Skin (2024)
Federal Grants 4 $1,190,838 total
Non-invasive automated wound analysis via deep learning neural networks
In vivo label-free characterization of aged skin to predict delayed wound healing
I-Corps: Skin autofluorescence imager for rapidly assessing skin wound healing
REU Site: Training in Emerging Biomedical Optics and Imaging Approaches
Collaboration Network
Top Collaborators
- Three-Dimensional Quantification of Collagen Microstructure During Tensile Mechanical Loading of Skin
- Improved segmentation of collagen second harmonic generation images with a deep learning convolutional neural network
- Neuro-regenerative behavior of adipose-derived stem cells in aligned collagen I hydrogels
- Mechanical Models of Collagen Networks for Understanding Changes in the Failure Properties of Aging Skin
- Multiscale Computational Model Predicts Mouse Skin Kinematics Under Tensile Loading
Showing 5 of 15 shared publications
- Three-Dimensional Quantification of Collagen Microstructure During Tensile Mechanical Loading of Skin
- Mechanical Models of Collagen Networks for Understanding Changes in the Failure Properties of Aging Skin
- Multiscale Computational Model Predicts Mouse Skin Kinematics Under Tensile Loading
- Quantifying age-related changes in the structure and mechanical function of skin with multiscale imaging
- Quantifying 3D tissue kinematics though second harmonic generation microscopy of skin during mechanical loading
Showing 5 of 7 shared publications
- Three-Dimensional Quantification of Collagen Microstructure During Tensile Mechanical Loading of Skin
- Automated Extraction of Skin Wound Healing Biomarkers From In Vivo Label‐Free Multiphoton Microscopy Using Convolutional Neural Networks
- Quantifying age-related changes in the structure and mechanical function of skin with multiscale imaging
- Quantifying 3D tissue kinematics though second harmonic generation microscopy of skin during mechanical loading
- Multimodal characterization of skin wound healing in vivo using label-free multiphoton microscopy
- Three-Dimensional Quantification of Collagen Microstructure During Tensile Mechanical Loading of Skin
- Mechanical Models of Collagen Networks for Understanding Changes in the Failure Properties of Aging Skin
- Multiscale Computational Model Predicts Mouse Skin Kinematics Under Tensile Loading
- Quantifying age-related changes in the structure and mechanical function of skin with multiscale imaging
- Quantifying 3D tissue kinematics though second harmonic generation microscopy of skin during mechanical loading
- Automated Extraction of Skin Wound Healing Biomarkers From In Vivo Label‐Free Multiphoton Microscopy Using Convolutional Neural Networks
- Autofluorescence lifetime of gelatin-methacrylate hydrogels is sensitive to changes in cross-linking and pH
- Multimodal characterization of skin wound healing in vivo using label-free multiphoton microscopy
- Single Dose of N-Acetylcysteine in Local Anesthesia Increases Expression of HIF1α, MAPK1, TGFβ1 and Growth Factors in Rat Wound Healing
- N-Acetylcysteine Added to Local Anesthesia Reduces Scar Area and Width in Early Wound Healing—An Animal Model Study
- Pre-Incisional and Multiple Intradermal Injection of N-Acetylcysteine Slightly Improves Incisional Wound Healing in an Animal Model
- Single Dose of N-Acetylcysteine in Local Anesthesia Increases Expression of HIF1α, MAPK1, TGFβ1 and Growth Factors in Rat Wound Healing
- N-Acetylcysteine Added to Local Anesthesia Reduces Scar Area and Width in Early Wound Healing—An Animal Model Study
- Pre-Incisional and Multiple Intradermal Injection of N-Acetylcysteine Slightly Improves Incisional Wound Healing in an Animal Model
- Single Dose of N-Acetylcysteine in Local Anesthesia Increases Expression of HIF1α, MAPK1, TGFβ1 and Growth Factors in Rat Wound Healing
- N-Acetylcysteine Added to Local Anesthesia Reduces Scar Area and Width in Early Wound Healing—An Animal Model Study
- Pre-Incisional and Multiple Intradermal Injection of N-Acetylcysteine Slightly Improves Incisional Wound Healing in an Animal Model
- Single Dose of N-Acetylcysteine in Local Anesthesia Increases Expression of HIF1α, MAPK1, TGFβ1 and Growth Factors in Rat Wound Healing
- N-Acetylcysteine Added to Local Anesthesia Reduces Scar Area and Width in Early Wound Healing—An Animal Model Study
- Pre-Incisional and Multiple Intradermal Injection of N-Acetylcysteine Slightly Improves Incisional Wound Healing in an Animal Model
- Neuro-regenerative behavior of adipose-derived stem cells in aligned collagen I hydrogels
- A three-dimensional valve-on-chip microphysiological system implicates cell cycle progression, cholesterol metabolism and protein homeostasis in early calcific aortic valve disease progression
- Neuro-Regenerative Behavior of Adipose-Derived Stem Cells in Aligned Collagen I Hydrogels
- Neuro-regenerative behavior of adipose-derived stem cells in aligned collagen I hydrogels
- A three-dimensional valve-on-chip microphysiological system implicates cell cycle progression, cholesterol metabolism and protein homeostasis in early calcific aortic valve disease progression
- Neuro-Regenerative Behavior of Adipose-Derived Stem Cells in Aligned Collagen I Hydrogels
- Label-Free Optical Metabolic Imaging in Cells and Tissues
- Tissue Imaging and Quantification Relying on Endogenous Contrast
- Label-Free Multiphoton Microscopy for the Detection and Monitoring of Calcific Aortic Valve Disease
- A three-dimensional valve-on-chip microphysiological system implicates cell cycle progression, cholesterol metabolism and protein homeostasis in early calcific aortic valve disease progression
- Label-Free Multiphoton Microscopy for the Detection and Monitoring of Calcific Aortic Valve Disease
- A three-dimensional valve-on-chip microphysiological system implicates cell cycle progression, cholesterol metabolism and protein homeostasis in early calcific aortic valve disease progression
- Single Dose of N-Acetylcysteine in Local Anesthesia Increases Expression of HIF1α, MAPK1, TGFβ1 and Growth Factors in Rat Wound Healing
- N-Acetylcysteine Added to Local Anesthesia Reduces Scar Area and Width in Early Wound Healing—An Animal Model Study
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