Literature DB >> 18163832

Optimized autofluorescence bronchoscopy using additional backscattered red light.

Tanja Gabrecht1, Thomas Glanzmann, Lutz Freitag, Bernd-Claus Weber, Hubert van den Bergh, Georges Wagnières.   

Abstract

Autofluorescence bronchoscopy (AFB) has been shown to be a highly sensitive tool for the detection of early endobronchial cancers. When excited with blue-violet light, early neoplasia in the bronchi tend to show a decrease of autofluorescence in the green region of the spectrum and a relatively smaller decrease in the red region of the spectrum. Superposing the green foreground image and the red background image creates the resultant autofluorescence image. Our aim was to investigate whether the addition of backscattered red light to the tissue autofluorescence signal could improve the contrast between healthy and diseased tissue. We have performed a clinical study involving 41 lung cancers using modified autofluorescence bronchoscopy systems. The lesions were examined sequentially with conventional violet autofluorescence excitation (430 nm+/-30 nm) and violet autofluorescence excitation plus backscattered red light (430 nm+/-40 nm plus 665 nm+/-15 nm). The contrast between (pre-)neoplastic and healthy tissue was quantified with off-line image analysis. We observed a 2.7 times higher contrast when backscattered red light was added to the violet excitation. In addition, the image quality was improved in terms of the signal-to-noise ratio (SNR) with this spectral design.

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Year:  2007        PMID: 18163832     DOI: 10.1117/1.2811952

Source DB:  PubMed          Journal:  J Biomed Opt        ISSN: 1083-3668            Impact factor:   3.170


  5 in total

Review 1.  Fluorescence lifetime techniques in medical applications.

Authors:  Laura Marcu
Journal:  Ann Biomed Eng       Date:  2012-01-25       Impact factor: 3.934

2.  Optimize Transfer Learning for Lung Diseases in Bronchoscopy Using a New Concept: Sequential Fine-Tuning.

Authors:  Tao Tan; Zhang Li; Haixia Liu; Farhad G Zanjani; Quchang Ouyang; Yuling Tang; Zheyu Hu; Qiang Li
Journal:  IEEE J Transl Eng Health Med       Date:  2018-08-16       Impact factor: 3.316

3.  Autofluorescence bronchoscopy: quantification of inter-patient variations of fluorescence intensity.

Authors:  Tanja Gabrecht; Blaise Lovisa; Huber van den Bergh; Georges Wagnières
Journal:  Lasers Med Sci       Date:  2007-11-30       Impact factor: 3.161

Review 4.  Advanced bronchoscopic techniques in diagnosis and staging of lung cancer.

Authors:  Bojan Zaric; Vladimir Stojsic; Tatjana Sarcev; Goran Stojanovic; Vladimir Carapic; Branislav Perin; Paul Zarogoulidis; Kaid Darwiche; Kosmas Tsakiridis; Ilias Karapantzos; Georgios Kesisis; Ioanna Kougioumtzi; Nikolaos Katsikogiannis; Nikolaos Machairiotis; Aikaterini Stylianaki; Christophoros N Foroulis; Konstantinos Zarogoulidis
Journal:  J Thorac Dis       Date:  2013-09       Impact factor: 2.895

5.  Combining deep learning and coherent anti-Stokes Raman scattering imaging for automated differential diagnosis of lung cancer.

Authors:  Sheng Weng; Xiaoyun Xu; Jiasong Li; Stephen T C Wong
Journal:  J Biomed Opt       Date:  2017-10       Impact factor: 3.170

  5 in total

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