Screening prostate cancer using a portable near infrared scanning imaging unit with an optical fiber-based rectal probe

2012 ◽  
Author(s):  
Yang Pu ◽  
Wubao Wang ◽  
Guichen Tang ◽  
Yury Budansky ◽  
Mikhail Sharonov ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Optical Fiber ◽  
Near Infrared ◽  
Infrared Scanning ◽  
Scanning Imaging

Large-core, high-bandwidth polymer optical fiber for near infrared use

1995 ◽  
Vol 7 (4) ◽  
pp. 403-405 ◽  
Author(s):  
T. Ishigure ◽  
E. Nihei ◽  
Y. Koike ◽  
C.E. Forbes ◽  
L. LaNieve ◽  
...  
Keyword(s):  
Optical Fiber ◽  
Near Infrared ◽  
Large Core ◽  
Polymer Optical Fiber ◽  
High Bandwidth

scholarly journals Prediction of non-recoverable collapse in Eucalyptus globulus from near infrared scanning of radial wood samples

2013 ◽  
Vol 71 (6) ◽  
pp. 755-768 ◽  
Author(s):  
Maximilian Wentzel-Vietheer ◽  
Russell Washusen ◽  
Geoffrey M. Downes ◽  
Christopher Harwood ◽  
Nicholas Ebdon ◽  
...  
Keyword(s):  
Eucalyptus Globulus ◽  
Near Infrared ◽  
Infrared Scanning

scholarly journals A targeted low molecular weight near-infrared fluorescent probe for prostate cancer

2010 ◽  
Vol 20 (23) ◽  
pp. 7124-7126 ◽  
Author(s):  
Tiancheng Liu ◽  
Lisa Y. Wu ◽  
Mark R. Hopkins ◽  
Joseph K. Choi ◽  
Clifford E. Berkman
Keyword(s):  
Prostate Cancer ◽  
Molecular Weight ◽  
Fluorescent Probe ◽  
Near Infrared ◽  
Low Molecular Weight

scholarly journals A linear method for the retrieval of sun-induced chlorophyll fluorescence from GOME-2 and SCIAMACHY data

2015 ◽  
Vol 8 (6) ◽  
pp. 2589-2608 ◽  
Author(s):  
P. Köhler ◽  
L. Guanter ◽  
J. Joiner
Keyword(s):  
Chlorophyll Fluorescence ◽  
Near Infrared ◽  
Linear Method ◽  
Data Sets ◽  
Good Correspondence ◽  
Retrieval Method ◽  
Elimination Algorithm ◽  
Backward Elimination ◽  
Scanning Imaging ◽  
Low Sensitivity

Abstract. Global retrievals of near-infrared sun-induced chlorophyll fluorescence (SIF) have been achieved in the last few years by means of a number of space-borne atmospheric spectrometers. Here, we present a new retrieval method for medium spectral resolution instruments such as the Global Ozone Monitoring Experiment-2 (GOME-2) and the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY). Building upon the previous work by Guanter et al. (2013) and Joiner et al. (2013), our approach provides a solution for the selection of the number of free parameters. In particular, a backward elimination algorithm is applied to optimize the number of coefficients to fit, which reduces also the retrieval noise and selects the number of state vector elements automatically. A sensitivity analysis with simulated spectra has been utilized to evaluate the performance of our retrieval approach. The method has also been applied to estimate SIF at 740 nm from real spectra from GOME-2 and for the first time, from SCIAMACHY. We find a good correspondence of the absolute SIF values and the spatial patterns from the two sensors, which suggests the robustness of the proposed retrieval method. In addition, we compare our results to existing SIF data sets, examine uncertainties and use our GOME-2 retrievals to show empirically the relatively low sensitivity of the SIF retrieval to cloud contamination.

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