Investigation of wavenumber calibration for Raman spectroscopy using a polymer standard

Liu, Dongyue; Byrne, Hugh J.; O’Neill, Luke A.J.; Hennelly, Bryan M.

doi:10.1117/12.2307574

Cited by 11 publications

(11 citation statements)

References 34 publications

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“…All spectra were recorded using the Andor Solis software plugin for Micro-Manager. The system was wave-number calibrated, using a polymer standard as described in [ 33 ]. No intensity calibration was performed for this experiment since all spectra were recorded from the same system.…”

Section: Methodsmentioning

confidence: 99%

Automated Raman Micro-Spectroscopy of Epithelial Cell Nuclei for High-Throughput Classification

O’Dwyer

Domijan

Dignam

et al. 2021

Cancers

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Raman micro-spectroscopy is a powerful technique for the identification and classification of cancer cells and tissues. In recent years, the application of Raman spectroscopy to detect bladder, cervical, and oral cytological samples has been reported to have an accuracy greater than that of standard pathology. However, despite being entirely non-invasive and relatively inexpensive, the slow recording time, and lack of reproducibility have prevented the clinical adoption of the technology. Here, we present an automated Raman cytology system that can facilitate high-throughput screening and improve reproducibility. The proposed system is designed to be integrated directly into the standard pathology clinic, taking into account their methodologies and consumables. The system employs image processing algorithms and integrated hardware/software architectures in order to achieve automation and is tested using the ThinPrep standard, including the use of glass slides, and a number of bladder cancer cell lines. The entire automation process is implemented, using the open source Micro-Manager platform and is made freely available. We believe that this code can be readily integrated into existing commercial Raman micro-spectrometers.

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Section: Methodsmentioning

confidence: 99%

Automated Raman Micro-Spectroscopy of Epithelial Cell Nuclei for High-Throughput Classification

O’Dwyer

Domijan

Dignam

et al. 2021

Cancers

View full text Add to dashboard Cite

show abstract

“…All spectra were recorded using the Andor Solis software plugin for Micro-Manager. The system was wavenumber calibrated using a polymer standard as described in [33]. No intensity calibration was performed for this experiment since all spectra were recorded from the same system.…”

Section: Methodsmentioning

confidence: 99%

Automated Raman micro-spectroscopy of epithelial cells for the high-throughput classification

O’Dwyer

Domijan

Dignam

et al. 2021

Preprint

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Raman micro-spectroscopy is a powerful technique for the identification and classification of cancer cells and tissues. In recent years, the application of Raman spectroscopy to detect bladder, cervical, and oral cytological samples has been reported to have an accuracy that is greater than standard pathology. However, despite being entirely non-invasive and relatively inexpensive, the slow recording time, and lack of reproducibility, have prevented the clinical adoption of the technology. Here we present an automated Raman cytology system that can facilitate high-throughput screening and improve reproducibility. The proposed system is designed to be integrated directly into the standard pathology clinic, taking into account their methodologies and consumables. The system employs image processing algorithms and integrated hardware/software architectures in order to achieve automation and is tested using the ThinPrep standard, including the use of glass slides, and a number of bladder cancer cell lines. The entire automation process is implemented using the open source Micro-Manager platform, and is made freely available. We believe this code can be readily integrated into existing commercial Raman micro-spectrometers.

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“…A polymer reference material, acquired from Ibidi GmbH, 34 was chosen as the first sample for investigation due to its thermal stability, resistance to photo-bleaching, and strong reliable signal, which reduces the overall experimental variability. The consistency of this sample and its insignificant baseline ensures an accurate assessment of the proposed CRA algorithm in terms of the S/N ratio.…”

Section: Materials and Methods Materialsmentioning

confidence: 99%

An Algorithm for the Removal of Cosmic Ray Artifacts in Spectral Data Sets

Barton

Hennelly

2019

Appl Spectrosc

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Cosmic ray artifacts may be present in all photo-electric readout systems. In spectroscopy, they present as random unidirectional sharp spikes that distort spectra and may have an affect on post-processing, possibly affecting the results of multivariate statistical classification. A number of methods have previously been proposed to remove cosmic ray artifacts from spectra but the goal of removing the artifacts while making no other change to the underlying spectrum is challenging. One of the most successful and commonly applied methods for the removal of comic ray artifacts involves the capture of two sequential spectra that are compared in order to identify spikes. The disadvantage of this approach is that at least two recordings are necessary, which may be problematic for dynamically changing spectra, and which can reduce the signal-to-noise (S/N) ratio when compared with a single recording of equivalent duration due to the inclusion of two instances of read noise. In this paper, a cosmic ray artefact removal algorithm is proposed that works in a similar way to the double acquisition method but requires only a single capture, so long as a data set of similar spectra is available. The method employs normalized covariance in order to identify a similar spectrum in the data set, from which a direct comparison reveals the presence of cosmic ray artifacts, which are then replaced with the corresponding values from the matching spectrum. The advantage of the proposed method over the double acquisition method is investigated in the context of the S/N ratio and is applied to various data sets of Raman spectra recorded from biological cells.

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Investigation of wavenumber calibration for Raman spectroscopy using a polymer standard

Cited by 11 publications

References 34 publications

Automated Raman Micro-Spectroscopy of Epithelial Cell Nuclei for High-Throughput Classification

Automated Raman Micro-Spectroscopy of Epithelial Cell Nuclei for High-Throughput Classification

Automated Raman micro-spectroscopy of epithelial cells for the high-throughput classification

An Algorithm for the Removal of Cosmic Ray Artifacts in Spectral Data Sets

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