Zobrazeno 1 - 10
of 58
pro vyhledávání: '"Shuna Cheng"'
Autor:
Taylor A. Hinsdale, Bilal H. Malik, Shuna Cheng, Oscar R. Benavides, Maryellen L. Giger, John M. Wright, Paras B. Patel, Javier A. Jo, Kristen C. Maitland
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
Abstract We demonstrate that structured illumination microscopy has the potential to enhance fluorescence lifetime imaging microscopy (FLIM) as an early detection method for oral squamous cell carcinoma. FLIM can be used to monitor or detect changes
Externí odkaz:
https://doaj.org/article/3fe4e94ea55946189c029db792ed761b
Autor:
Elvis Duran-Sierra, Shuna Cheng, Rodrigo Cuenca, Beena Ahmed, Jim Ji, Vladislav V. Yakovlev, Mathias Martinez, Moustafa Al-Khalil, Hussain Al-Enazi, Yi-Shing Lisa Cheng, John Wright, Carlos Busso, Javier A. Jo
Publikováno v:
Cancers, Vol 13, Iss 19, p 4751 (2021)
Multispectral autofluorescence lifetime imaging (maFLIM) can be used to clinically image a plurality of metabolic and biochemical autofluorescence biomarkers of oral epithelial dysplasia and cancer. This study tested the hypothesis that maFLIM-derive
Externí odkaz:
https://doaj.org/article/17f89b496c9d496db471635b545bb59b
Publikováno v:
BioResources, Vol 9, Iss 4, Pp 7653-7665 (2014)
The effect of different physico-chemical treatments used in the isolation process of aloe vera (AV) rind nanofibers on the tensile properties of the nanofiber films were studied to understand the root of the low strength values of these films. In the
Externí odkaz:
https://doaj.org/article/eeff38474ca24ca1be8df4cc577fca7e
Autor:
Kayla Caughlin, Elvis Duran-Sierra, Shuna Cheng, Rodrigo Cuenca, Beena Ahmed, Jim Ji, Mathias Martinez, Moustafa Al-Khalil, Hussain Al-Enazi, Yi-Shing Lisa Cheng, John Wright, Javier A. Jo, Carlos Busso
Publikováno v:
IEEE Journal of Biomedical and Health Informatics. 27:457-468
Deep learning approaches for medical image analysis are limited by small data set size due to multiple factors such as patient privacy and difficulties in obtaining expert labelling for each image. In medical imaging system development pipelines, pha
Autor:
Elvis Duran, Shuna Cheng, Rodrigo Cuenca, Beena Ahmed, Jim Ji, Vladislav V. Yakovlev, Mathias Martinez, Moustafa Al-Khalil, Hussain Al-Enazi, Y.S. Lisa Cheng, John Wright, Carlos Busso, Javier A. Jo
Publikováno v:
Imaging, Therapeutics, and Advanced Technology in Head and Neck Surgery and Otolaryngology 2022.
Autor:
Elvis Duran, Shuna Cheng, Rodrigo Cuenca, Beena Ahmed, Jim Ji, Vladislav V. Yakovlev, Mathias Martinez, Moustafa Al-Khalil, Hussain Al-Enazi, Y.S. Lisa Cheng, John Wright, Carlos Busso, Javier A. Jo
Publikováno v:
Imaging, Therapeutics, and Advanced Technology in Head and Neck Surgery and Otolaryngology 2022.
Autor:
Kayla, Caughlin, Elvis, Duran-Sierra, Shuna, Cheng, Rodrigo, Cuenca, Beena, Ahmed, Jim, Ji, Vladislav V, Yakovlev, Mathias, Martinez, Moustafa, Al-Khalil, Hussain, Al-Enazi, Javier A, Jo, Carlos, Busso
Publikováno v:
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).
In contrast to previous studies that focused on classical machine learning algorithms and hand-crafted features, we present an end-to-end neural network classification method able to accommodate lesion heterogeneity for improved oral cancer diagnosis
Autor:
Elvis Duran-Sierra, Shuna Cheng, Rodrigo Cuenca, Beena Ahmed, Jim Ji, Vladislav V. Yakovlev, Mathias Martinez, Moustafa Al-Khalil, Hussain Al-Enazi, Javier A. Jo
Publikováno v:
Biomed Opt Express
Early detection is critical for improving the survival rate and quality of life of oral cancer patients; unfortunately, dysplastic and early-stage cancerous oral lesions are often difficult to distinguish from oral benign lesions during standard clin
Autor:
Taylor Hinsdale, Maryellen L. Giger, Kristen C. Maitland, Bilal H. Malik, John M. Wright, Shuna Cheng, Javier A. Jo, Oscar R. Benavides, Paras B. Patel
Publikováno v:
Scientific Reports
Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
We demonstrate that structured illumination microscopy has the potential to enhance fluorescence lifetime imaging microscopy (FLIM) as an early detection method for oral squamous cell carcinoma. FLIM can be used to monitor or detect changes in the fl
Publikováno v:
Optical Imaging, Therapeutics, and Advanced Technology in Head and Neck Surgery and Otolaryngology 2019.
We present our 2nd generation handheld simultaneous multispectral frequency-domain FLIM endoscopic system for label-free metabolic imaging of oral cancer, with enhanced optical performance and system usability. Our custom-designed and 3D-printed hand