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Cancer Imaging. Topics in Bioengineering. The present and future role of cancer imaging. Fass L. (2008) Mol Oncol . Figures 1 & 2. Shrinidhi. Michael. Urano et al. (2011) Science Transl Med. Figure 1. Michael. Urano et al. (2011) Science Transl Med. Figure 1. Paige. - PowerPoint PPT Presentation

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Spinal Cord Injury

Cancer ImagingTopics in BioengineeringThe present and future role of cancer imaging

Fass L. (2008) Mol Oncol. Figures 1 & 2

ShrinidhiUrano et al. (2011) Science Transl Med. Figure 1Michael

Urano et al. (2011) Science Transl Med. Figure 1Michael

Urano et al. (2011) Science Transl Med. Figure 2Paige

Anna

Urano et al. (2011) Science Transl Med. Figure 3Urano et al. (2011) Science Transl Med. Figure 4

FelixKevinUrano et al. (2011) Science Transl Med. Figure 5

Urano et al. (2011) Science Transl Med. Figure 5Inseong

Urano et al. (2011) Science Transl Med. Figure 6Urano et al. (2011) Science Transl Med. Supplementary Data Movies!!!http://stm.sciencemag.org/content/3/110/110ra119/suppl/DC1 Video S1(.mov format). Dynamic fluorescence endoscopy of SHIN3 metastases.Video S2(.mov format). Dynamic fluorescence endoscopy of SKOV3 metastases.Video S3(.mov format). Dynamic fluorescence endoscopy of OVCAR3 metastases.Video S4(.mov format). Dynamic fluorescence endoscopy of OVCAR4 metastases.Video S5(.mov format). Dynamic fluorescence endoscopy of OVCAR5 metastases.Video S6(.mov format). Dynamic fluorescence endoscopy of OVCAR8 metastases.Video S7(.mov format). Fluorescence endoscopy of six ovarian cancer metastases 60 min after spraying the gGlu-HMRG probe.Video S8(.mov format). Dynamic fluorescence endoscopyguided biopsy of tiny peritoneal SHIN3 ovarian metastases.

Michaelhttp://www.ucl.ac.uk/surgicalscience/departments_research/gsrg/nmlc/newsarchive http://www.docstoc.com/docs/84445901/Elastic-Scattering-Spectroscopy-_-Light-Scattering-Spectroscopy- Elastic Scattering Spectroscopy

Non-dysplastic intestinal metaplasia

High grade dysplasiaZhu et al. (2009) J Biomed Opt. Figure 1Paige

Zhu et al. (2009) J Biomed Opt. Figure 2Shrinidhi

Zhu et al. (2009) J Biomed Opt. Figure 3Anna

http://en.wikipedia.org/wiki/Principal_component_analysis Principal Component AnalysisUsed for predictive modelsConverts set of observations (data) of possibly correlated variables into values of linearly uncorrelated (ie, orthogonal) variables (principal components)First PC accounts for as much of variability in data as possible, each subsequent PC is less (and still orthogonal)Reveals internal structure of data in a way that best describes its variance

Zhu et al. (2009) J Biomed Opt. Figure 4Felix

Zhu et al. (2009) J Biomed Opt. Figure 5Kevin

Zhu et al. (2009) J Biomed Opt. Table 1Zhu et al. (2009) J Biomed Opt. Figure 6Maura