| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Henderson, Alex
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (15/15 displayed)
- 2022Infrared micro-spectroscopy coupled with multivariate and machine learning techniques for cancer classification in tissue: a comparison of classification method, performance, and pre-processing techniquecitations
- 2016Evaluation of biomolecular distributions in rat brain tissues by means of ToF-SIMS using a continuous beam of Ar clusterscitations
- 2015Mass spectrometric imaging of brain tissue by time-of-flight secondary ion mass spectrometry - How do polyatomic primary beams C 60 + , Ar 2000 + , water-doped Ar 2000 + and (H 2 O) 6000 + compare?citations
- 2015Mass spectrometric imaging of brain tissue by time-of-flight secondary ion mass spectrometry – How do polyatomic primary beams C60+, Ar2000+, water-doped Ar2000+ and (H2O)6000+ compare?citations
- 2013Time-of-flight SIMS as a novel approach to unlocking the hypoxic properties of cancercitations
- 2013Peptide structural analysis using continuous Ar cluster and C60 ion beamscitations
- 2013Peptide structural analysis using continuous Ar cluster and C60 ion beamscitations
- 2013Peak picking as a pre-processing technique for imaging time of flight secondary ion mass spectrometrycitations
- 2013ToF-SIMS as a tool for metabolic profiling small biomolecules in cancer systemscitations
- 2012Peak picking as a pre-processing technique for imaging time of flight secondary ion mass spectrometry
- 2011Interactive spatio-spectral analysis of three-dimensional mass-spectral (3DxMS) chemical imagescitations
- 2011Three-dimensional mass spectral imaging of HeLa-M cells - Sample preparation, data interpretation and visualisationcitations
- 2009A comparison of PCA and MAF for ToF-SIMS image interpretationcitations
- 2008A new dynamic in mass spectral imaging of single biological cellscitations
- 2004ToF-SIMS studies of sulfuric acid hydrate filmscitations
Places of action
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article
Infrared micro-spectroscopy coupled with multivariate and machine learning techniques for cancer classification in tissue: a comparison of classification method, performance, and pre-processing technique
Abstract
The visual detection, classification, and differentiation of cancers within tissues of clinical patients is an extremely difficult and time-consuming process with severe diagnosis implications. To this end, many computational approaches have been developed to analyse tissue samples to supplement histological cancer diagnoses. One approach is the interrogation of the chemical composition of the actual tissue samples through the utilisation of vibrational spectroscopy, specifically Infrared (IR) spectroscopy. Cancerous tissue can be detected by analysing the molecular vibration patterns of tissues undergoing IR irradiation, and even graded, with multivariate and Machine Learning (ML) techniques. This publication serves to review and highlight the potential for the application of infrared microscopy techniques such as Fourier Transform Infrared Spectroscopy (FTIR) and Quantum Cascade Laser Infrared Spectroscopy (QCL), as a means to improve diagnostic accuracy and allow earlier detection of human neoplastic disease. This review provides an overview of the detection and classification of different cancerous tissues using FTIR spectroscopy paired with multivariate and ML techniques, using the F1-Score as a quantitative metric for direct comparison of model performances. Comparisons also extend to data handling techniques, with a provision of a suggested pre-processing protocol for future studies alongside suggestions as to reporting standards for future publication.