ArticleJournal of biomedical optics2023
Open-sourced Raman spectroscopy data processing package implementing a baseline removal algorithm validated from multiple datasets acquired in human tissue and biofluids.
Article in Journal of biomedical optics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed, 58 citations in OpenAlex.
- Shining a light on brain tumors: a review of Raman spectroscopy in the operating room.Journal of biomedical optics · 2026Review
- An Integrated Raman Platform with Embedded AI for Intraoperative Real-Time Cancer Detection.Analytical chemistry · 2026Article
- Label-free wide-field imaging of brain tumors using near-infrared endogenous fluorescence and reflectance normalization.Journal of biomedical optics · 2026Article
- Combining label-free Raman spectroscopy with machine learning to monitor COVID-19 disease from acute infection to recovery.Journal of biomedical optics · 2026Article
- Raman Spectroscopy for Probing Pathological Protein Aggregates: Potential and Perspectives for Advanced Diagnostic Applications.International journal of molecular sciences · 2026Review
- Raman Spectroscopy Combined with Machine Learning Reveals Myalgic Encephalomyelitis-Associated Biomolecular Signatures at Rest and After Standardized Stress.International journal of molecular sciences · 2026Article
- Article
- Combining label-free Raman spectroscopy and machine learning to identify early biomarkers of COVID-19 disease severity and mortality.Journal of biomedical optics · 2026Article
- RamEx: an R package for high-throughput microbial ramanome analyses with accurate quality assessment.Microbiome · 2026Article
- Experimental method to assess depth sensing limits of inelastic scattering measurements using spatial-offset Raman spectroscopy imaging.Journal of biomedical optics · 2025Article
- Artificial Intelligence-Powered Raman Spectroscopy through Open Science and FAIR Principles.ACS nano · 2025Review
- StreamFind: data processing workflows for qualification and quantification of biopharmaceutical drug products analyzed by size exclusion chromatography coupled to capillary-enhanced Raman spectroscopy.Analytical and bioanalytical chemistry · 2025Article
- Deployment of a real-time prostate cancer confirmation system with Raman spectroscopy: fine-tuning versus test-time adaptation of 1D CNNs.Biophotonics discovery · 2025Article
- Intraoperative use of high-speed Raman spectroscopy during soft tissue sarcoma resection.Scientific reports · 2025Article
- Development and preclinical evaluation of an endonasal Raman spectroscopy probe for transsphenoidal pituitary adenoma surgery.Journal of biomedical optics · 2025Article
- Preliminary study demonstrating cancer cells detection at the margins of whole glioblastoma specimens with Raman spectroscopy imaging.Scientific reports · 2025Article
- Quantitative assessment of the generalizability of a brain tumor Raman spectroscopy machine learning model to various tumor types including astrocytoma and oligodendroglioma.Journal of biomedical optics · 2025Article
- Single-cell Raman spectroscopy detects pediatric focal cortical dysplasia.Biophotonics discovery · 2025Article
- Enhanced spectral resolution and reduced acquisition time in fiber-based wavelength-swept source Raman spectroscopy.Neurophotonics · 2025Article
- Advancing SERS as a quantitative technique: challenges, considerations, and correlative approaches to aid validation.Nano convergence · 2024Review
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
Significance: Standardized data processing approaches are required in the field of bio-Raman spectroscopy to ensure information associated with spectral data acquired by different research groups, and with different systems, can be compared on an equal footing. Aim: An open-sourced data processing software package was developed, implementing algorithms associated with all steps required to isolate the inelastic scattering component from signals acquired using Raman spectroscopy devices. The package includes a novel morphological baseline removal technique (BubbleFill) that provides increased adaptability to complex baseline shapes compared to current gold standard techniques. Also incorporated in the package is a versatile tool simulating spectroscopic data with varying levels of Raman signal-to-background ratios, baselines with different morphologies, and varying levels of stochastic noise. Results: Application of the BubbleFill technique to simulated data demonstrated superior baseline removal performance compared to standard algorithms, including iModPoly and MorphBR. The data processing workflow of the open-sourced package was validated in four independent in-human datasets, demonstrating it leads to inter-systems data compatibility. Conclusions: A new open-sourced spectroscopic data pre-processing package was validated on simulated and real-world in-human data and is now available to researchers and clinicians for the development of new clinical applications using Raman spectroscopy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.