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Single-Step Preprocessing of Raman Spectra Using Convolutional Neural Networks
Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, Strömningslära och experimentell mekanik.ORCID-id: 0000-0003-1845-6199
Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, Strömningslära och experimentell mekanik.ORCID-id: 0000-0003-4879-8261
Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, Strömningslära och experimentell mekanik.ORCID-id: 0000-0003-3268-1691
2020 (engelsk)Inngår i: Applied Spectroscopy, ISSN 0003-7028, E-ISSN 1943-3530, Vol. 74, nr 4, s. 427-438Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Preprocessing of Raman spectra is generally done in three separate steps: (1) cosmic ray removal, (2) signal smoothing, and (3) baseline subtraction. We show that a convolutional neural network (CNN) can be trained using simulated data to handle all steps in one operation. First, synthetic spectra are created by randomly adding peaks, baseline, mixing of peaks and baseline with background noise, and cosmic rays. Second, a CNN is trained on synthetic spectra and known peaks. The results from preprocessing were generally of higher quality than what was achieved using a reference based on standardized methods (second-difference, asymmetric least squares, cross-validation). From 105 simulated observations, 91.4% predictions had smaller absolute error (RMSE), 90.3% had improved quality (SSIM), and 94.5% had reduced signal-to-noise (SNR) power. The CNN preprocessing generated reliable results on measured Raman spectra from polyethylene, paraffin and ethanol with background contamination from polystyrene. The result shows a promising proof of concept for the automated preprocessing of Raman spectra.

sted, utgiver, år, opplag, sider
Sage Publications, 2020. Vol. 74, nr 4, s. 427-438
Emneord [en]
Raman spectroscopy, convolutional neural network, CNN, preprocessing, simulated data, chemometrics, deep learning
HSV kategori
Forskningsprogram
Experimentell mekanik
Identifikatorer
URN: urn:nbn:se:ltu:diva-77138DOI: 10.1177/0003702819888949ISI: 000508787000001PubMedID: 31961223Scopus ID: 2-s2.0-85078087556OAI: oai:DiVA.org:ltu-77138DiVA, id: diva2:1377289
Forskningsfinansiär
Swedish Foundation for Strategic Research , ITM17-0056Swedish Research Council, 2016-04220
Merknad

Validerad;2020;Nivå 2;2020-04-16 (alebob)

Tilgjengelig fra: 2019-12-11 Laget: 2019-12-11 Sist oppdatert: 2023-09-05bibliografisk kontrollert
Inngår i avhandling
1. Development of Methods to Investigate Pulmonary Arterial Smooth Muscle Cells under Hypoxia
Åpne denne publikasjonen i ny fane eller vindu >>Development of Methods to Investigate Pulmonary Arterial Smooth Muscle Cells under Hypoxia
2019 (engelsk)Licentiatavhandling, med artikler (Annet vitenskapelig)
Abstract [en]

Hypoxic pulmonary vasoconstriction (HPV) is a physiological response to localized alveolarhypoxia that is intrinsic to the pulmonary circulation. By hypoxia-induced contractionof pulmonary arterial smooth muscle cells (PASMCs), the pulmonary capillary bloodflow is redirected to alveolar areas of high oxygen partial pressure, thus maintaining theventilation-perfusion ratio. Although the principle of HPV was recognized decades agothe underlying pathway remains elusive. The patch clamp technique, imaging and Ramanspectroscopy are methods that can be used to investigate parts of the mechanisms. Toenable measurements at controlled oxygen concentrations a gas-tight microfluidic systemwas developed. In this thesis preparatory experiments to couple the gas-tight systemto a microscope that enabled simultaneous measurements with patch clamp, imagingand Raman spectroscopy are discussed. The patch clamp technique is to be used formeasurements on the dynamics of the ion-channels in the cellular membrane as well aschanges in membrane potential as a response to hypoxia. Imaging of PASMCs is requiredto successfully apply the patch clamp technique. Further, imaging will also reveal whetherthe mechanical response of HPV has been triggered, for this purpose image analysis forestimation of optical flow can be used. Raman spectroscopy enables measurements ofbiochemical changes in redox biomarkers, cytochrome c and NADH, of the mitochondrialelectron transport chain. This thesis shows that the gas-tight microfluidic system providesoptimal control of the oxygen content, in an experimantal setting where the patch clamptechnique can be applied. Raman measurements showed significantly larger variationsin spectra compared to an open fluidic system, which is the conventional approach.However, the results showed a need for improved Raman preprocessing. For this purposea Convolutional Neural Network (CNN) was trained using synthetic spectra that providedoptimal reconstruction of the Raman signal. Finally, simultaneous imaging and Ramanspectroscopy of red blood cells were performed in a home built microscope. The resultspave the way for measurements on PASMCs.

sted, utgiver, år, opplag, sider
Luleå: Luleå University of Technology, 2019
Serie
Licentiate thesis / Luleå University of Technology, ISSN 1402-1757
HSV kategori
Forskningsprogram
Experimentell mekanik
Identifikatorer
urn:nbn:se:ltu:diva-77140 (URN)978-91-7790-513-4 (ISBN)978-91-7790-514-1 (ISBN)
Presentation
2020-01-24, E237, Luleå, 10:00 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2019-12-11 Laget: 2019-12-11 Sist oppdatert: 2023-09-05bibliografisk kontrollert
2. Multimodal applications in medical technology that utilize Raman spectroscopy
Åpne denne publikasjonen i ny fane eller vindu >>Multimodal applications in medical technology that utilize Raman spectroscopy
2022 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Alternativ tittel[en]
Raman spectroscopy in multimodal applications to medical technology
Abstract [en]

Biology can often be explained by structures and interactions between molecules. It is therefore of importance for medical sciences that the chemical reactions and molecular compositions of biological samples can be measured. The purpose of this thesis is twofold. Firstly, to develop methods for measuring the underlying mechanisms of the lung disorder pulmonary hypertension. Secondly, to investigating the possibility of classifying brain tissue for safer resection of brain tumors. A multimodal approach is often motivated, as there exist many different measurement techniques. In this thesis Raman spectroscopy has been applied both as the main measurement modality and in cooperation with other methods.

Raman spectroscopy is a label free optical measurement technique that measure inelastic scattering from materials that are illuminated by a monochromatic light source. Raman scattering results in a weak signal that is uniquely proportional to the chemical structure of the sample. When measuring biological samples, Raman scattering is accompanied by a strong intrinsic fluorescent signature that can overshadow the signal. To elucidate the underlying Raman spectrum, it is generally preprocessed to allow further analysis. There are many methods available for preprocessing; a selection of commonly used methodologies has been included here, as well as methods of my own design. The most novel approach being a neural network that was trained on synthetic spectra to perform preprocessing without relying on user defined variables, which is common for other methods (Paper A). The neural network resulted in improved preprocessing when compared to a control predictor, with test data from paraffin, ethanol, and polyethylene, as well as spectra based on simulations.

Hypoxic pulmonary hypertension (PH) is a condition where the arteries in the lung-walls are blocked due to prolonged oxygen deprivation or lung disease. People who suffer from PH, often experience shortness of breath and fatigue. If the condition persists the added strain upon the heart from the increased resistance in the arteries will result in right-heart failure. Hypoxic PH is the result of permanently constricted pulmonary arterial smooth muscle cells (PASMCs). PASMCs reside in the arterial walls and react locally to reduced oxygen content by constricting. This effect is called pulmonary vasoconstriction (HPV) and results in the regulation of deoxygenated blood to areas of the lung that have more oxygen available. Full understanding of the mechanisms of oxygen sensing in PASMCs has importance for the development of new treatments against PH. To this end a sealed microfluidic system was designed with the purpose to enable multimodal measurements of the response of cultivated PASMCs to acute hypoxia including Raman spectroscopy, patch clamp, and imaging (Paper B).  The microfluidic system was initially tested using Raman spectroscopy and oxygen sensing to investigate the reaction of PASMCs to hypoxia. The results were compared to an open flow system that showed a higher variation of the desired oxygen content (21% or 4%) compared to the designed closed microfluidic system. The system was later reworked and tested with simultaneous measurements using Raman spectroscopy, oxygen sensing, imaging, and patch-clamp (Paper C). With this setup it was possible to track the molecular response in the mitochondria in correlation with the activity of the calcium-ion channels and the mechanical response of the PASMCs.

The main modality used in clinics for brain tumor imaging is magnetic resonance imaging (MRI). Structural MRI gives neurosurgeons information regarding the size and mass effects of tumors. However, during surgery it can be difficult to assess the marginal zone of tumors. Improvements have been made by incorporating fluorescence guided resection (FGR) in the standard practice of many operating rooms in Europe. FGR relies on measuring the emission from metabolized precursor molecules. However, the drawback of FGR is that it is not tumor specific and has reduced sensitivity in low-grade tumors and children. In this thesis the option of incorporating a Raman probe setup, to fill in the gaps of other methods has been discussed. During this preliminary discussion it was noted that there is no standard approach for preprocessing and many different methodologies have been employed by various researcher. Therefore, measurement on fresh brain tumor tissue from a Raman microscopy setup was preprocessed using commonly applied methods, in addition to a pretrained neural network, to investigate the variations of the outcome (Paper D). It became apparent that different methods and variable choices can alter the distinctive spectral features. The conclusion being that it is important to be both transparent and specific when explaining how data has been prepared prior to analysis to enable reproducible results.

sted, utgiver, år, opplag, sider
Luleå: Luleå University of Technology, 2022
Serie
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
Emneord
Raman spectroscopy, Preprocessing, Pulmonary arterial smooth muscle cells, Brain tumors
HSV kategori
Forskningsprogram
Experimentell mekanik
Identifikatorer
urn:nbn:se:ltu:diva-87915 (URN)978-91-7790-981-1 (ISBN)978-91-7790-982-8 (ISBN)
Disputas
2022-02-04, E632, Luleå, 09:00 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2021-11-16 Laget: 2021-11-16 Sist oppdatert: 2025-02-09bibliografisk kontrollert

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