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/sl/article/autofluorescence-bronchoscopy-image-processing-in-the-selected-colour-spaces/>. Date accessed: 04 nov. 2024. 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/sl/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/sl/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. 04 Nov. 2024
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/sl/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/sl/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/sl/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)
Strojniški vestnik - Journal of Mechanical Engineering 58(2012)9, 501-508
© The Authors, CC-BY 4.0 Int. Change in copyright policy from 2022, Jan 1st.
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.