Autofluorescence Bronchoscopy Image Processing in the Selected Colour Spaces

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FINKŠT, Tomaž ;TASIČ, Jurij Franc ;ZORMAN-TERČELJ, Marjeta ;ZAJC, Matej .
Autofluorescence Bronchoscopy Image Processing in the Selected Colour Spaces. 
Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 58, n.9, p. 501-508, june 2018. 
ISSN 0039-2480.
Available at: <https://www.sv-jme.eu/article/autofluorescence-bronchoscopy-image-processing-in-the-selected-colour-spaces/>. Date accessed: 21 feb. 2020. 
doi:http://dx.doi.org/10.5545/sv-jme.2012.350.
Finkšt, T., Tasič, J., Zorman-Terčelj, M., & Zajc, M.
(2012).
Autofluorescence Bronchoscopy Image Processing in the Selected Colour Spaces.
Strojniški vestnik - Journal of Mechanical Engineering, 58(9), 501-508.
doi:http://dx.doi.org/10.5545/sv-jme.2012.350
@article{sv-jmesv-jme.2012.350,
	author = {Tomaž  Finkšt and Jurij Franc  Tasič and Marjeta  Zorman-Terčelj and Matej  Zajc},
	title = {Autofluorescence Bronchoscopy Image Processing in the Selected Colour Spaces},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {58},
	number = {9},
	year = {2012},
	keywords = {colour spaces; image processing; image acquisition; image segmentation; edge detection; autofluorescence bronchoscopy},
	abstract = {Reading diagnostic medical images usually requires the expertise of a specialist physician. To aid physicians we have developed an algorithm that deduces medical information by analysing colour nuances of an image obtained by bronchoscopy. The goal is to ensure a high probability of detecting bronchial cancer. Autofluorescent bronchoscopy images are analysed by the proposed algorithm. The machine-made diagnoses of early cancer stages are highly correlated with the diagnoses made by a medical expert. Reading the image using a specialized apparatus and producing a pre-diagnosis by image-recognition software and a special set of rules has the potential to produce automated second opinions for most cases of the disease.},
	issn = {0039-2480},	pages = {501-508},	doi = {10.5545/sv-jme.2012.350},
	url = {https://www.sv-jme.eu/article/autofluorescence-bronchoscopy-image-processing-in-the-selected-colour-spaces/}
}
Finkšt, T.,Tasič, J.,Zorman-Terčelj, M.,Zajc, M.
2012 June 58. Autofluorescence Bronchoscopy Image Processing in the Selected Colour Spaces. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 58:9
%A Finkšt, Tomaž 
%A Tasič, Jurij Franc 
%A Zorman-Terčelj, Marjeta 
%A Zajc, Matej 
%D 2012
%T Autofluorescence Bronchoscopy Image Processing in the Selected Colour Spaces
%B 2012
%9 colour spaces; image processing; image acquisition; image segmentation; edge detection; autofluorescence bronchoscopy
%! Autofluorescence Bronchoscopy Image Processing in the Selected Colour Spaces
%K colour spaces; image processing; image acquisition; image segmentation; edge detection; autofluorescence bronchoscopy
%X Reading diagnostic medical images usually requires the expertise of a specialist physician. To aid physicians we have developed an algorithm that deduces medical information by analysing colour nuances of an image obtained by bronchoscopy. The goal is to ensure a high probability of detecting bronchial cancer. Autofluorescent bronchoscopy images are analysed by the proposed algorithm. The machine-made diagnoses of early cancer stages are highly correlated with the diagnoses made by a medical expert. Reading the image using a specialized apparatus and producing a pre-diagnosis by image-recognition software and a special set of rules has the potential to produce automated second opinions for most cases of the disease.
%U https://www.sv-jme.eu/article/autofluorescence-bronchoscopy-image-processing-in-the-selected-colour-spaces/
%0 Journal Article
%R 10.5545/sv-jme.2012.350
%& 501
%P 8
%J Strojniški vestnik - Journal of Mechanical Engineering
%V 58
%N 9
%@ 0039-2480
%8 2018-06-28
%7 2018-06-28
Finkšt, Tomaž, Jurij Franc  Tasič, Marjeta  Zorman-Terčelj, & Matej  Zajc.
"Autofluorescence Bronchoscopy Image Processing in the Selected Colour Spaces." Strojniški vestnik - Journal of Mechanical Engineering [Online], 58.9 (2012): 501-508. Web.  21 Feb. 2020
TY  - JOUR
AU  - Finkšt, Tomaž 
AU  - Tasič, Jurij Franc 
AU  - Zorman-Terčelj, Marjeta 
AU  - Zajc, Matej 
PY  - 2012
TI  - Autofluorescence Bronchoscopy Image Processing in the Selected Colour Spaces
JF  - Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2012.350
KW  - colour spaces; image processing; image acquisition; image segmentation; edge detection; autofluorescence bronchoscopy
N2  - Reading diagnostic medical images usually requires the expertise of a specialist physician. To aid physicians we have developed an algorithm that deduces medical information by analysing colour nuances of an image obtained by bronchoscopy. The goal is to ensure a high probability of detecting bronchial cancer. Autofluorescent bronchoscopy images are analysed by the proposed algorithm. The machine-made diagnoses of early cancer stages are highly correlated with the diagnoses made by a medical expert. Reading the image using a specialized apparatus and producing a pre-diagnosis by image-recognition software and a special set of rules has the potential to produce automated second opinions for most cases of the disease.
UR  - https://www.sv-jme.eu/article/autofluorescence-bronchoscopy-image-processing-in-the-selected-colour-spaces/
@article{{sv-jme}{sv-jme.2012.350},
	author = {Finkšt, T., Tasič, J., Zorman-Terčelj, M., Zajc, M.},
	title = {Autofluorescence Bronchoscopy Image Processing in the Selected Colour Spaces},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {58},
	number = {9},
	year = {2012},
	doi = {10.5545/sv-jme.2012.350},
	url = {https://www.sv-jme.eu/article/autofluorescence-bronchoscopy-image-processing-in-the-selected-colour-spaces/}
}
TY  - JOUR
AU  - Finkšt, Tomaž 
AU  - Tasič, Jurij Franc 
AU  - Zorman-Terčelj, Marjeta 
AU  - Zajc, Matej 
PY  - 2018/06/28
TI  - Autofluorescence Bronchoscopy Image Processing in the Selected Colour Spaces
JF  - Strojniški vestnik - Journal of Mechanical Engineering; Vol 58, No 9 (2012): Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2012.350
KW  - colour spaces, image processing, image acquisition, image segmentation, edge detection, autofluorescence bronchoscopy
N2  - Reading diagnostic medical images usually requires the expertise of a specialist physician. To aid physicians we have developed an algorithm that deduces medical information by analysing colour nuances of an image obtained by bronchoscopy. The goal is to ensure a high probability of detecting bronchial cancer. Autofluorescent bronchoscopy images are analysed by the proposed algorithm. The machine-made diagnoses of early cancer stages are highly correlated with the diagnoses made by a medical expert. Reading the image using a specialized apparatus and producing a pre-diagnosis by image-recognition software and a special set of rules has the potential to produce automated second opinions for most cases of the disease.
UR  - https://www.sv-jme.eu/article/autofluorescence-bronchoscopy-image-processing-in-the-selected-colour-spaces/
Finkšt, Tomaž, Tasič, Jurij Franc, Zorman-Terčelj, Marjeta, AND Zajc, Matej.
"Autofluorescence Bronchoscopy Image Processing in the Selected Colour Spaces" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 58 Number 9 (28 June 2018)

Authors

Affiliations

  • University of Ljubljana Faculty of Mechanical Engineering Laboratory for digital systems and electrotechnics 1
  • University of Ljubljana Faculty of Electrical Engineering Digital Signal, Image and Video Processing Laboratory 2
  • University Medical Centre Ljubljana, Department of Pulmonary Diseases and Allergy 3

Paper's information

Strojniški vestnik - Journal of Mechanical Engineering 58(2012)9, 501-508

https://doi.org/10.5545/sv-jme.2012.350

Reading diagnostic medical images usually requires the expertise of a specialist physician. To aid physicians we have developed an algorithm that deduces medical information by analysing colour nuances of an image obtained by bronchoscopy. The goal is to ensure a high probability of detecting bronchial cancer. Autofluorescent bronchoscopy images are analysed by the proposed algorithm. The machine-made diagnoses of early cancer stages are highly correlated with the diagnoses made by a medical expert. Reading the image using a specialized apparatus and producing a pre-diagnosis by image-recognition software and a special set of rules has the potential to produce automated second opinions for most cases of the disease.

colour spaces; image processing; image acquisition; image segmentation; edge detection; autofluorescence bronchoscopy