Multimodal Optical Diagnostics of Cancer

[1]  Karl Pearson F.R.S..  LIII. On lines and planes of closest fit to systems of points in space , 1901 .

[2]  S. C. Johnson.  Hierarchical clustering schemes , 1967, Psychometrika.

[3]  J. Bezdek,et al.  FCM: The fuzzy c-means clustering algorithm , 1984 .

[4]  Roderick P. McDonald,et al.  Factor Analysis and Related Methods , 1985 .

[5]  A. O’Keefe,et al.  Cavity ring‐down optical spectrometer for absorption measurements using pulsed laser sources , 1988 .

[6]  N. Dubrawsky.  Cancer statistics , 1989, CA: a cancer journal for clinicians.

[7]  L. Nafie,et al.  Raman optical activity. , 1993, Methods in enzymology.

[8]  Johann Gasteiger,et al.  Neural Networks for Chemists: An Introduction , 1993 .

[9]  Philip A. Martin,et al.  Tunable diode laser monitoring of atmospheric trace gas constituents , 1995 .

[10]  F. Harren,et al.  Geometrical optimization of a longitudinal resonant photoacoustic cell for sensitive and fast trace gas detection , 1996 .

[11]  Suppression of the etalon fringe in absorption spectrometry with an infrared tunable diode laser , 1997 .

[12]  M. Phillips.  Method for the collection and assay of volatile organic compounds in breath. , 1997, Analytical biochemistry.

[13]  Klaus-Robert Müller,et al.  Asymptotic statistical theory of overtraining and cross-validation , 1997, IEEE Trans. Neural Networks.

[14]  A. Hansel,et al.  On-line monitoring of volatile organic compounds at pptv levels by means of proton-transfer-reaction mass spectrometry (PTR-MS) medical applications, food control and environmental research , 1998 .

[15]  Recommendations for Standardized Procedures for the Online and Offline Measurement of Exhaled Lower Respiratory Nitric Oxide and Nasal Nitric Oxide in Adults and Children — 1999 , 1999 .

[16]  R. Cataneo,et al.  Volatile organic compounds in breath as markers of lung cancer: a cross-sectional study , 1999, The Lancet.

[17]  A. Gordin,et al.  SnifProbe: new method and device for vapor and gas sampling. , 2000, Journal of chromatography. A.

[18]  A. Miklós,et al.  Application of acoustic resonators in photoacoustic trace gas analysis and metrology , 2001 .

[19]  M. Ringnér,et al.  Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks , 2001, Nature Medicine.

[20]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[21]  Kilian Q. Weinberger,et al.  Learning a kernel matrix for nonlinear dimensionality reduction , 2004, ICML.

[22]  Corinna Cortes,et al.  Support-Vector Networks , 1995, Machine Learning.

[23]  J. Kingsbury.  The Illustrated Wavelet Transform Handbook: Introductory Theory and Applications in Science, Engineering, Medicine and Finance , 2004 .

[24]  Amitabha Mukerjee,et al.  Non-linear Dimensionality Reduction by Locally Linear Isomaps , 2004, ICONIP.

[25]  P. Mazzone,et al.  Detection of lung cancer by sensor array analyses of exhaled breath. , 2005, American journal of respiratory and critical care medicine.

[26]  Mahesh Pal,et al.  Random forest classifier for remote sensing classification , 2005 .

[27]  A. Romain,et al.  Microbial volatile organic compounds as indicators of fungi. Can an electronic nose detect fungi in indoor environments , 2005 .

[28]  Solid phase microextraction for analysis of alkanes and aromatic hydrocarbons in human breath. , 2005, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

[29]  L. Bianchi,et al.  Exhaled volatile organic compounds in patients with non-small cell lung cancer: cross sectional and nested short-term follow-up study , 2005, Respiratory research.

[30]  Ping Wang,et al.  A study of an electronic nose for detection of lung cancer based on a virtual SAW gas sensors array and imaging recognition method , 2005 .

[31]  J. Hankinson,et al.  Standardisation of the single-breath determination of carbon monoxide uptake in the lung , 2005, European Respiratory Journal.

[32]  W. Cao,et al.  Breath analysis: potential for clinical diagnosis and exposure assessment. , 2006, Clinical chemistry.

[33]  Stéphane Lafon,et al.  Diffusion maps , 2006 .

[34]  P. Schoenmakers,et al.  Automatic selection of optimal Savitzky-Golay smoothing. , 2006, Analytical chemistry.

[35]  P. Polavarapu.  Determination of molecular stereochemistry using optical rotatory dispersion, vibrational circular dichroism and vibrational Raman optical activity , 2006 .

[36]  Ralf Klinkenberg,et al.  Boosting classifiers for drifting concepts , 2007, Intell. Data Anal..

[37]  P. Španěl,et al.  The challenge of breath analysis for clinical diagnosis and therapeutic monitoring. , 2007, The Analyst.

[38]  V. A. Kapitanov,et al.  High-sensitivity laser photoacoustic leak detector , 2007 .

[39]  Michel Verleysen,et al.  Nonlinear Dimensionality Reduction , 2021, Computer Vision.

[40]  A Gelperin,et al.  Nanotube-based sensor arrays for clinical breath analysis , 2008, Journal of breath research.

[41]  J. Austin,et al.  Detection of lung cancer using weighted digital analysis of breath biomarkers. , 2008, Clinica chimica acta; international journal of clinical chemistry.

[42]  G. Pioggia,et al.  Implementation of Fowler's method for end-tidal air sampling , 2008, Journal of breath research.

[43]  M. Fiegl,et al.  Noninvasive detection of lung cancer by analysis of exhaled breath , 2009, BMC Cancer.

[44]  B. Buszewski,et al.  Analysis of exhaled breath from smokers, passive smokers and non-smokers by solid-phase microextraction gas chromatography/mass spectrometry. , 2009, Biomedical chromatography : BMC.

[45]  K. Rabe,et al.  Comparison of exhaled breath condensate pH using two commercially available devices in healthy controls, asthma and COPD patients , 2009, Respiratory research.

[46]  J. D. de Gouw,et al.  Airborne measurements of ethene from industrial sources using laser photo-acoustic spectroscopy. , 2009, Environmental science & technology.

[47]  K. Schwarz,et al.  Determining concentration patterns of volatile compounds in exhaled breath by PTR-MS , 2009, Journal of breath research.

[48]  G. Sun,et al.  Quantitative breath analysis of volatile organic compounds of lung cancer patients. , 2010, Lung cancer.

[49]  R. Dweik,et al.  Clinical applications of breath testing , 2010, F1000 medicine reports.

[50]  M. Frank,et al.  Human breath analysis: methods for sample collection and reduction of localized background effects , 2010, Analytical and bioanalytical chemistry.

[51]  W. Miekisch,et al.  Breath biomarkers for lung cancer detection and assessment of smoking related effects--confounding variables, influence of normalization and statistical algorithms. , 2010, Clinica chimica acta; international journal of clinical chemistry.

[52]  Witold R. Rudnicki,et al.  Feature Selection with the Boruta Package , 2010 .

[53]  Alphus D. Wilson,et al.  Advances in Electronic-Nose Technologies Developed for Biomedical Applications , 2011, Sensors.

[54]  B. Buszewski,et al.  The application of statistical methods using VOCs to identify patients with lung cancer , 2011, Journal of breath research.

[55]  Q. Jöbsis,et al.  Clinical use of exhaled volatile organic compounds in pulmonary diseases: a systematic review , 2012, Respiratory Research.

[56]  H. Zeng,et al.  A comparison of spectroscopic techniques for human breath analysis , 2012 .

[57]  Yu. V. Kistenev,et al.  The system for dehumidification of samples in laser gas analysis , 2012 .

[58]  H. Barr,et al.  Advances in the clinical application of Raman spectroscopy for cancer diagnostics. , 2013, Photodiagnosis and photodynamic therapy.

[59]  Neha Mehra,et al.  Survey on Multiclass Classification Methods , 2013 .

[60]  P. Chaturvedi,et al.  In vivo Raman spectroscopy for detection of oral neoplasia: A pilot clinical study , 2014, Journal of biophotonics.

[61]  H. Haick,et al.  Assessment of the exhalation kinetics of volatile cancer biomarkers based on their physicochemical properties , 2014, Journal of breath research.

[62]  Oleg O. Myakinin,et al.  Combined Raman spectroscopy and autofluoresence imaging method for in vivo skin tumor diagnosis , 2014, Optics & Photonics - Optical Engineering + Applications.

[63]  Mia K Markey,et al.  Clinical study of noninvasive in vivo melanoma and nonmelanoma skin cancers using multimodal spectral diagnosis , 2014, Journal of biomedical optics.

[64]  C. Murali Krishna,et al.  Classification of oral cancers using Raman spectroscopy of serum , 2014, Photonics West - Biomedical Optics.

[65]  Leanne M. Fullwood,et al.  Investigating the use of Raman and immersion Raman spectroscopy for spectral histopathology of metastatic brain cancer and primary sites of origin , 2014 .

[66]  C. Murali Krishna,et al.  In vivo Raman spectroscopy of human uterine cervix: exploring the utility of vagina as an internal control , 2014, Journal of biomedical optics.

[67]  M. Pacheco,et al.  Discrimination of prostate carcinoma from benign prostate tissue fragments in vitro by estimating the gross biochemical alterations through Raman spectroscopy , 2014, Lasers in Medical Science.

[68]  Wei Zheng,et al.  Near-infrared Raman spectroscopy for assessing biochemical changes of cervical tissue associated with precarcinogenic transformation. , 2014, The Analyst.

[69]  B. Costello,et al.  The human volatilome: volatile organic compounds (VOCs) in exhaled breath, skin emanations, urine, feces and saliva , 2014, Journal of breath research.

[70]  Knipfer Christian,et al.  Raman difference spectroscopy: a non-invasive method for identification of oral squamous cell carcinoma. , 2014, Biomedical optics express.

[71]  Oliver A. C. Stevens,et al.  Endoscopic Raman spectroscopy enables objective diagnosis of dysplasia in Barrett's esophagus. , 2014, Gastrointestinal endoscopy.

[72]  B. Yan,et al.  An intraoperative diagnosis of parotid gland tumors using Raman spectroscopy and support vector machine , 2014 .

[73]  Mohd Yasser,et al.  Raman Spectroscopic Study of Radioresistant Oral Cancer Sublines Established by Fractionated Ionizing Radiation , 2014, PloS one.

[74]  A. A. Karapuzikov,et al.  LaserBreeze gas analyzer for noninvasive diagnostics of air exhaled by patients , 2014 .

[75]  G. Lloyd,et al.  Evaluation of a confocal Raman probe for pathological diagnosis during colonoscopy , 2014, Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland.

[76]  Mads S. Bergholt,et al.  Real-time depth-resolved fiber optic Raman endoscopy for in vivo diagnosis of gastric precancer , 2014, Photonics West - Biomedical Optics.

[77]  Oleg O. Myakinin,et al.  Two-step Raman spectroscopy method for tumor diagnosis , 2014, Photonics Europe.

[78]  G. Lloyd,et al.  Utilising non-consensus pathology measurements to improve the diagnosis of oesophageal cancer using a Raman spectroscopic probe. , 2014, The Analyst.

[79]  C. Murali Krishna,et al.  In vivo Raman spectroscopy of cervix cancers , 2014, Photonics West - Biomedical Optics.

[80]  Yasuhiro Maeda,et al.  Measurement of the human esophageal cancer in an early stage with Raman spectroscopy , 2014, Photonics West - Biomedical Optics.

[81]  Mads S. Bergholt,et al.  Fiberoptic confocal raman spectroscopy for real-time in vivo diagnosis of dysplasia in Barrett's esophagus. , 2014, Gastroenterology.

[82]  Guangjun Zhang,et al.  Classification for breast cancer diagnosis with Raman spectroscopy. , 2014, Biomedical optics express.

[83]  J. Desroches,et al.  Characterization of a Raman spectroscopy probe system for intraoperative brain tissue classification. , 2015, Biomedical optics express.

[84]  H. Zeng,et al.  Pilot study: Raman spectroscopy in differentiating premalignant and malignant oral lesions from normal mucosa and benign lesions in humans , 2015, Head & neck.

[85]  A. Wilson.  Advances in Electronic-Nose Technologies for the Detection of Volatile Biomarker Metabolites in the Human Breath , 2015, Metabolites.

[86]  M. Pacheco,et al.  Discrimination of non‐melanoma skin lesions from non‐tumor human skin tissues in vivo using Raman spectroscopy and multivariate statistics , 2015, Lasers in surgery and medicine.

[87]  Mads S. Bergholt,et al.  Characterizing variability of in vivo Raman spectroscopic properties of different anatomical sites of normal colorectal tissue towards cancer diagnosis at colonoscopy. , 2015, Analytical chemistry.

[88]  A. Synytsya,et al.  The potential of chiroptical and vibrational spectroscopy of blood plasma for the discrimination between colon cancer patients and the control group. , 2015, The Analyst.

[89]  C. Krishna,et al.  Recurrence prediction in oral cancers: a serum Raman spectroscopy study. , 2015, The Analyst.

[90]  A. A. Karapuzikov,et al.  Methods of spectral analysis of exhaled air suitable for routine diagnostics of diseases of the respiratory system , 2015 .

[91]  L. Bernstein,et al.  Intraoperative brain cancer detection with Raman spectroscopy in humans , 2015, Science Translational Medicine.

[92]  I. Gersonde,et al.  In vivo study for the discrimination of cancerous and normal skin using fibre probe‐based Raman spectroscopy , 2015, Experimental dermatology.

[93]  Xiaohua Sun,et al.  Detection of volatile organic compounds (VOCs) from exhaled breath as noninvasive methods for cancer diagnosis , 2016, Analytical and Bioanalytical Chemistry.

[94]  M. Teh,et al.  Comparative study of the endoscope-based bevelled and volume fiber-optic Raman probes for optical diagnosis of gastric dysplasia in vivo at endoscopy , 2015, Analytical and Bioanalytical Chemistry.

[95]  H. Lui,et al.  Real-time Raman spectroscopy for automatic in vivo skin cancer detection: an independent validation , 2015, Analytical and Bioanalytical Chemistry.

[96]  P. Chaturvedi,et al.  Raman spectroscopy and cytopathology of oral exfoliated cells for oral cancer diagnosis , 2015 .

[97]  M. P. Fernandes,et al.  Early Detection of Lung Cancer Using Nano-Nose - A Review , 2015, The open biomedical engineering journal.

[98]  M. Teh,et al.  Simultaneous fingerprint and high-wavenumber fiber-optic Raman spectroscopy improves in vivo diagnosis of esophageal squamous cell carcinoma at endoscopy , 2015, Scientific Reports.

[99]  P. Sterk,et al.  Breathomics in lung disease. , 2015, Chest.

[100]  D. Vrazhnov,et al.  Wavelet based de-noising of breath air absorption spectra profiles for improved classification by principal component analysis , 2015 .

[101]  Qing-bo Li,et al.  Discrimination of Breast Cancer from Normal Tissue with Raman Spectroscopy and Chemometrics , 2015 .

[102]  A. Engel,et al.  An automated gas chromatography time-of-flight mass spectrometry instrument for the quantitative analysis of halocarbons in air , 2015 .

[103]  D. A. Vrazhnov,et al.  Applications of principal component analysis to breath air absorption spectra profiles classification , 2015, Atomic and Molecular Pulsed Lasers.

[104]  I. Horváth,et al.  Established methodological issues in electronic nose research: how far are we from using these instruments in clinical settings of breath analysis? , 2015, Journal of breath research.

[105]  S. Ganesan,et al.  Polarized Raman spectroscopy unravels the biomolecular structural changes in cervical cancer. , 2016, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[106]  Holly J. Butler,et al.  Feature driven classification of Raman spectra for real-time spectral brain tumour diagnosis using sound. , 2017, The Analyst.

[107]  Kevin Petrecca,et al.  Neural networks improve brain cancer detection with Raman spectroscopy in the presence of operating room light artifacts , 2016, Journal of biomedical optics.

[108]  Aamir Ahmad,et al.  Lung Cancer and Personalized Medicine , 2016, Advances in Experimental Medicine and Biology.

[109]  Oliver A.H. Jones,et al.  A Review of Analytical Techniques and Their Application in Disease Diagnosis in Breathomics and Salivaomics Research , 2016, International journal of molecular sciences.

[110]  M. Teh,et al.  Fiber-optic Raman spectroscopy for in vivo diagnosis of gastric dysplasia. , 2016, Faraday discussions.

[111]  Mads S. Bergholt,et al.  Simultaneous fingerprint and high‐wavenumber fiber‐optic Raman spectroscopy enhances real‐time in vivo diagnosis of adenomatous polyps during colonoscopy , 2016, Journal of biophotonics.

[112]  J. Kuo,et al.  Detection of Human Brain Tumor Infiltration With Quantitative Stimulated Raman Scattering Microscopy. , 2016, Neurosurgery.

[113]  B. Parvitte,et al.  Photoacoustic Detection of Methane in Large Concentrations with a Helmholtz Sensor: Simulation and Experimentation , 2016 .

[114]  Wei Zheng,et al.  Real-time in vivo diagnosis of laryngeal carcinoma with rapid fiber-optic Raman spectroscopy. , 2016, Biomedical optics express.

[115]  Marleen de Bruijne,et al.  Machine learning approaches in medical image analysis: From detection to diagnosis , 2016, Medical Image Anal..

[116]  Anita Mahadevan-Jansen,et al.  Clinical instrumentation and applications of Raman spectroscopy. , 2016, Chemical Society reviews.

[117]  Stephen T. C. Wong,et al.  Combining deep learning and coherent anti-Stokes Raman scattering imaging for automated differential diagnosis of lung cancer , 2017, Journal of biomedical optics.

[118]  Poonam Gera,et al.  Raman exfoliative cytology for oral precancer diagnosis , 2017, Journal of biomedical optics.

[119]  Yury V Kistenev,et al.  Exhaled air analysis using wideband wave number tuning range infrared laser photoacoustic spectroscopy , 2017, Journal of biomedical optics.

[120]  Jiemin Zhou,et al.  Review of recent developments in determining volatile organic compounds in exhaled breath as biomarkers for lung cancer diagnosis. , 2017, Analytica chimica acta.

[121]  S. Kozlov,et al.  In Vivo Diagnostics of Malignant and Benign Tumors with Low-Cost Raman Spectrometer , 2017 .

[122]  K. Asano,et al.  Clinical contributions of exhaled volatile organic compounds in the diagnosis of lung cancer , 2017, PloS one.

[123]  Hesham K. Yosef,et al.  Noninvasive Diagnosis of High-Grade Urothelial Carcinoma in Urine by Raman Spectral Imaging. , 2017, Analytical chemistry.

[124]  S. Holler,et al.  Raman Spectroscopy of Head and Neck Cancer: Separation of Malignant and Healthy Tissue Using Signatures Outside the “Fingerprint” Region , 2017, Biosensors.

[125]  G. Hanna,et al.  Optimisation of sampling parameters for standardised exhaled breath sampling , 2017, Journal of breath research.

[126]  Zhi Xu,et al.  Diagnosis of Breast Cancer Tissues Using 785 nm Miniature Raman Spectrometer and Pattern Regression , 2017, Sensors.

[127]  F. Lyng,et al.  Development of a high throughput (HT) Raman spectroscopy method for rapid screening of liquid blood plasma from prostate cancer patients. , 2017, The Analyst.

[128]  Lim Chwee Ming,et al.  Real time near-infrared Raman spectroscopy for the diagnosis of nasopharyngeal cancer , 2017, Oncotarget.

[129]  Zhi-ning Wen,et al.  Evaluating oral epithelial dysplasia classification system by near-infrared Raman spectroscopy. , 2017, Oncotarget.

[130]  A dual-tone modulation method to reduce the background fluctuation in tunable diode laser absorption spectroscopy , 2017 .

[131]  Wei Guo,et al.  Image Classification Based on Convolutional Denoising Sparse Autoencoder , 2017 .

[132]  K. Gerwert,et al.  Raman fiber-optical method for colon cancer detection: Cross-validation and outlier identification approach. , 2017, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[133]  S. Lam,et al.  Real‐time endoscopic Raman spectroscopy for in vivo early lung cancer detection , 2017, Journal of biophotonics.

[134]  Valery P Zakharov,et al.  Combined Raman and autofluorescence ex vivo diagnostics of skin cancer in near-infrared and visible regions , 2017, Journal of biomedical optics.

[135]  Elena Casiraghi,et al.  A novel computational method for automatic segmentation, quantification and comparative analysis of immunohistochemically labeled tissue sections , 2018, BMC Bioinformatics.

[136]  Guannan Chen,et al.  Autofluorescence and white light imaging‐guided endoscopic Raman and diffuse reflectance spectroscopy for in vivo nasopharyngeal cancer detection , 2018, Journal of biophotonics.

[137]  A. V. Shapovalov,et al.  Development of Classification Rules for a Screening Diagnostics of Lung Cancer Patients Based on the Spectral Analysis of Metabolic Profiles in the Exhaled Air , 2018 .

[138]  Xiaotong Zhang,et al.  Mathematical Methods and Algorithms for Improving Near-Infrared Tunable Diode-Laser Absorption Spectroscopy , 2018, Sensors.

[139]  M. Snuderl,et al.  Rapid Intraoperative Diagnosis of Pediatric Brain Tumors Using Stimulated Raman Histology. , 2018, Cancer research.

[140]  F. Saad,et al.  Mesoscopic characterization of prostate cancer using Raman spectroscopy: potential for diagnostics and therapeutics , 2018, BJU international.

[141]  Laser photoacoustic spectroscopy applications in breathomics , 2019, Journal of Biomedical Photonics & Engineering.