85,463 research outputs found
Nonscanning large-area Raman imaging for ex vivo/in vivo skin cancer discrimination
Imaging Raman spectroscopy can be used to identify cancerous tissue.
Traditionally, a step-by-step scanning of the sample is applied to generate a
Raman image, which, however, is too slow for routine examination of patients.
By transferring the technique of integral field spectroscopy (IFS) from
astronomy to Raman imaging, it becomes possible to record entire Raman images
quickly within a single exposure, without the need for a tedious scanning
procedure. An IFS-based Raman imaging setup is presented, which is capable of
measuring skin ex vivo or in vivo. It is demonstrated how Raman images of
healthy and cancerous skin biopsies were recorded and analyzed
Confocal Raman image method with maximum likelihood method
With the increasing interest in nano microscopic area, such as DNA sequencing, micro structure detection of molecular nano devices, a higher requirement for the spatial resolution of Raman spectroscopy is demanded. However, because of the weak Raman signal, the pinhole size of confocal Raman microscopy is usually a few hundreds microns to ensure a relatively higher spectrum throughput, but the large pinhole size limits the improvements of spatial resolution of confoal Raman spectroscopy. As a result, the convential confocal Raman spectroscopy has been unable to meet the needs of science development. Therefore, a confocal Raman image method with Maximum Likelihood image restoration algorithm based on the convential confocal Raman microscope is propose. This method combines super-resolution image restoration technology and confocal Raman microscopy to realize super-resolution imaging, by using Maximum Likelihood image restoration algorithm based on Poisson-Markov model to conduct image restoration processing on the Raman image, and the high frequency information of the image is recovered, and then the spatial resolution of Raman image is improved and the super-resolution image is realized. Simulation analyses and experimental results indicate that the proposed confocal Raman image method with Maximum Likelihood image restoration algorithm can improve the spatial resolution to 200 nm without losing any Raman spectral signal under the same condition with convential confocal Raman microscopy, moreover it has strong noise suppression capability. In conclusion, the method can provide a new approach for material science, life sciences, biomedicine and other frontiers areas. This method is an effective confocal Raman image method with high spatial resolution
High-Resolution Near-Field Raman Microscopy of Single-Walled Carbon Nanotubes
We present near-field Raman spectroscopy and imaging of single isolated single-walled carbon nanotubes with a spatial resolution of ≈25 nm. The near-field origin of the image contrast is confirmed by the measured dependence of the Raman scattering signal on tip-sample distance and the unique polarization properties. The method is used to study local variations in the Raman spectrum along a single single-walled carbon nanotube
Combined information from Raman spectroscopy and optical coherence tomography for enhanced diagnostic accuracy in tissue discrimination
We thank the UK EPSRC for funding, the CR-UK/EPSRC/MRC/DoH (England) imaging programme, the European Union project FAMOS (FP7 ICT, contract no. 317744) and the European Union project IIIOS (FP7/2007-2013, contract no. 238802). We thank Tayside Tissue Bank for providing us with the tissue samples under request number TR000289. K.D. is a Royal Society-Wolfson Merit Award Holder.Optical spectroscopy and imaging methods have proved to have potential to discriminate between normal and abnormal tissue types through minimally invasive procedures. Raman spectroscopy and Optical Coherence Tomography (OCT) provides chemical and morphological information of tissues respectively, which are complementary to each other. When used individually they might not be able to obtain high enough sensitivity and specificity that is clinically relevant. In this study we combined Raman spectroscopy information with information obtained from OCT to enhance the sensitivity and specificity in discriminating between Colonic Adenocarcinoma from Normal Colon. OCT being an imaging technique, the information from this technique is conventionally analyzed qualitatively. To combine with Raman spectroscopy information, it was essential to quantify the morphological information obtained from OCT. Texture analysis was used to extract information from OCT images, which in-turn was combined with the information obtained from Raman spectroscopy. The sensitivity and specificity of the classifier was estimated using leave one out cross validation (LOOCV) method where support vector machine (SVM) was used for binary classification of the tissues. The sensitivity obtained using Raman spectroscopy and OCT individually was 89% and 78% respectively and the specificity was 77% and 74% respectively. Combining the information derived using the two techniques increased both sensitivity and specificity to 94% demonstrating that combining complementary optical information enhances diagnostic accuracy. These results demonstrate that a multimodal approach using Raman-OCT would be able to enhance the diagnostic accuracy for identifying normal and cancerous tissue types.Publisher PD
A holistic multimodal approach to the non-invasive analysis of watercolour paintings
A holistic approach using non-invasive multimodal imaging and spectroscopic techniques to study the materials (pigments, drawing materials and paper) and painting techniques of watercolour paintings is presented. The non-invasive imaging and spectroscopic techniques include VIS-NIR reflectance spectroscopy and multispectral imaging, micro-Raman spectroscopy, X-ray fluorescence spectroscopy (XRF) and optical coherence tomography (OCT). The three spectroscopic techniques complement each other in pigment identification. Multispectral imaging (near infrared bands), OCT and micro-Raman complement each other in the visualisation and identification of the drawing material. OCT probes the microstructure and light scattering properties of the substrate while XRF detects the elemental composition that indicates the sizing methods and the filler content . The multiple techniques were applied in a study of forty six 19th century Chinese export watercolours from the Victoria & Albert Museum (V&A) and the Royal Horticultural Society (RHS) to examine to what extent the non-invasive analysis techniques employed complement each other and how much useful information about the paintings can be extracted to address art conservation and history questions
Non-invasive Scanning Raman Spectroscopy and Tomography for Graphene Membrane Characterization
Graphene has extraordinary mechanical and electronic properties, making it a
promising material for membrane based nanoelectromechanical systems (NEMS).
Here, chemical-vapor-deposited graphene is transferred onto target substrates
to suspend it over cavities and trenches for pressure-sensor applications. The
development of such devices requires suitable metrology methods, i.e.,
large-scale characterization techniques, to confirm and analyze successful
graphene transfer with intact suspended graphene membranes. We propose fast and
noninvasive Raman spectroscopy mapping to distinguish between freestanding and
substrate-supported graphene, utilizing the different strain and doping levels.
The technique is expanded to combine two-dimensional area scans with
cross-sectional Raman spectroscopy, resulting in three-dimensional Raman
tomography of membrane-based graphene NEMS. The potential of Raman tomography
for in-line monitoring is further demonstrated with a methodology for automated
data analysis to spatially resolve the material composition in micrometer-scale
integrated devices, including free-standing and substrate-supported graphene.
Raman tomography may be applied to devices composed of other two-dimensional
materials as well as silicon micro- and nanoelectromechanical systems.Comment: 23 pages, 5 figure
Applications Of Microspectroscopy, Hyperspectral Chemical Imaging And Fluorescence Microscopy In Chemistry, Biochemistry, Biotechnology, Molecular And Cell Biology
Chemical imaging is a technique for the simultaneous measurement of spectra (chemical information) and images or pictures (spatial information)^1,2^. The technique is most often applied to either solid or gel samples, and has applications in chemistry, biology^3-8^, medicine^9,10^, pharmacy^11^ (see also for example: Chemical Imaging Without Dyeing), food science, Food Physical Chemistry, Biotechnology^12,13^, Agriculture and industry. NIR, IR and Raman chemical imaging is also referred to as hyperspectral, spectroscopic, spectral or multi-spectral imaging (also see micro-spectroscopy). However, other ultra-sensitive and selective, chemical imaging techniques are also in use that involve either UV-visible or fluorescence microspectroscopy
Improving spatial resolution of confocal Raman microscopy by super-resolution image restoration
A new super-resolution image restoration confocal Raman microscopy method (SRIR-RAMAN) is proposed for improving the spatial resolution of confocal Raman microscopy. This method can recover the lost high spatial frequency of the confocal Raman microscopy by using Poisson-MAP super-resolution imaging restoration, thereby improving the spatial resolution of confocal Raman microscopy and realizing its super-resolution imaging. Simulation analyses and experimental results indicate that the spatial resolution of SRIR-RAMAN can be improved by 65% to achieve 200 nm with the same confocal Raman microscopy system. This method can provide a new tool for high spatial resolution micro-probe structure detection in physical chemistry, materials science, biomedical science and other areas
- …