Matches in SemOpenAlex for { <https://semopenalex.org/work/W3137705145> ?p ?o ?g. }
- W3137705145 abstract "Sub-diffuse optical properties may serve as useful cancer biomarkers, and wide-field heatmaps of these properties could aid physicians in identifying cancerous tissue. Sub-diffuse spatial frequency domain imaging (sd-SFDI) can reveal such wide-field maps, but the current time cost of experimentally validated methods for rendering these heatmaps precludes this technology from potential real-time applications.Our study renders heatmaps of sub-diffuse optical properties from experimental sd-SFDI images in real time and reports these properties for cancerous and normal skin tissue subtypes.A phase function sampling method was used to simulate sd-SFDI spectra over a wide range of optical properties. A machine learning model trained on these simulations and tested on tissue phantoms was used to render sub-diffuse optical property heatmaps from sd-SFDI images of cancerous and normal skin tissue.The model accurately rendered heatmaps from experimental sd-SFDI images in real time. In addition, heatmaps of a small number of tissue samples are presented to inform hypotheses on sub-diffuse optical property differences across skin tissue subtypes.These results bring the overall process of sd-SFDI a fundamental step closer to real-time speeds and set a foundation for future real-time medical applications of sd-SFDI such as image guided surgery." @default.
- W3137705145 created "2021-03-29" @default.
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- W3137705145 date "2021-09-23" @default.
- W3137705145 modified "2023-09-30" @default.
- W3137705145 title "Imaging sub-diffuse optical properties of cancerous and normal skin tissue using machine learning-aided spatial frequency domain imaging" @default.
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- W3137705145 doi "https://doi.org/10.1117/1.jbo.26.9.096007" @default.
- W3137705145 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8459901" @default.
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- W3137705145 hasPublicationYear "2021" @default.
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