Supervised Visual System for Recognition of Erythema Migrans, an Early Skin Manifestation of Lyme Borreliosis

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Izvoz citacije: ABNT
ČUK, Erik ;GAMS, Matjaž ;MOŽEK, Matej ;STRLE, Franc ;MARASPIN ČARMAN, Vera ;TASIČ, Jurij F..
Supervised Visual System for Recognition of Erythema Migrans, an Early Skin Manifestation of Lyme Borreliosis. 
Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 60, n.2, p. 115-123, june 2018. 
ISSN 0039-2480.
Available at: <https://www.sv-jme.eu/sl/article/supervised-visual-system-for-recognition-of-erythema-migrans-an-early-skin-manifestation-of-lyme-borreliosis/>. Date accessed: 21 oct. 2020. 
doi:http://dx.doi.org/10.5545/sv-jme.2013.1046.
Čuk, E., Gams, M., Možek, M., Strle, F., Maraspin Čarman, V., & Tasič, J.
(2014).
Supervised Visual System for Recognition of Erythema Migrans, an Early Skin Manifestation of Lyme Borreliosis.
Strojniški vestnik - Journal of Mechanical Engineering, 60(2), 115-123.
doi:http://dx.doi.org/10.5545/sv-jme.2013.1046
@article{sv-jmesv-jme.2013.1046,
	author = {Erik  Čuk and Matjaž  Gams and Matej  Možek and Franc  Strle and Vera  Maraspin Čarman and Jurij F. Tasič},
	title = {Supervised Visual System for Recognition of Erythema Migrans, an Early Skin Manifestation of Lyme Borreliosis},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {60},
	number = {2},
	year = {2014},
	keywords = {Lyme borreliosis, erythema migrans, finger draw, segmentation, recognition, attributes},
	abstract = {Lyme borreliosis is the most common human tick-borne infectious disease in the northern hemisphere, occurring predominantly in temperate regions of North America, Europe and Asia. The disease’s most frequent manifestation is erythema migrans, a skin lesion that appears within days to weeks of a tick bite. Early recognition of the lesion is important since it enables proper management and thus prevention of later consequences of the disease which can hamper normal life. In this article, a novel visual system for recognition of erythema migrans is presented based on new technology of smartphones. For detecting erythema migrans edge, we compared three different methods: GrowCut, Maximal Similarity Based Region Merging and Random Walker segmentation method. We have found that the results obtained with GrowCut method are better than those obtained with Random Walker method. Also the GrowCut method, improved with our new figure draw (FD1) marker yields comparable results to those obtained with Maximal Similarity Based Region Merging method. Several classification algorithms Naive Bayes, Support Vector Machine, Adaboost, Random forest and Neural network were compared and used for classification of skin lesions into ellipse, the most common shape of erythema migrans and erythema migrans class.},
	issn = {0039-2480},	pages = {115-123},	doi = {10.5545/sv-jme.2013.1046},
	url = {https://www.sv-jme.eu/sl/article/supervised-visual-system-for-recognition-of-erythema-migrans-an-early-skin-manifestation-of-lyme-borreliosis/}
}
Čuk, E.,Gams, M.,Možek, M.,Strle, F.,Maraspin Čarman, V.,Tasič, J.
2014 June 60. Supervised Visual System for Recognition of Erythema Migrans, an Early Skin Manifestation of Lyme Borreliosis. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 60:2
%A Čuk, Erik 
%A Gams, Matjaž 
%A Možek, Matej 
%A Strle, Franc 
%A Maraspin Čarman, Vera 
%A Tasič, Jurij F.
%D 2014
%T Supervised Visual System for Recognition of Erythema Migrans, an Early Skin Manifestation of Lyme Borreliosis
%B 2014
%9 Lyme borreliosis, erythema migrans, finger draw, segmentation, recognition, attributes
%! Supervised Visual System for Recognition of Erythema Migrans, an Early Skin Manifestation of Lyme Borreliosis
%K Lyme borreliosis, erythema migrans, finger draw, segmentation, recognition, attributes
%X Lyme borreliosis is the most common human tick-borne infectious disease in the northern hemisphere, occurring predominantly in temperate regions of North America, Europe and Asia. The disease’s most frequent manifestation is erythema migrans, a skin lesion that appears within days to weeks of a tick bite. Early recognition of the lesion is important since it enables proper management and thus prevention of later consequences of the disease which can hamper normal life. In this article, a novel visual system for recognition of erythema migrans is presented based on new technology of smartphones. For detecting erythema migrans edge, we compared three different methods: GrowCut, Maximal Similarity Based Region Merging and Random Walker segmentation method. We have found that the results obtained with GrowCut method are better than those obtained with Random Walker method. Also the GrowCut method, improved with our new figure draw (FD1) marker yields comparable results to those obtained with Maximal Similarity Based Region Merging method. Several classification algorithms Naive Bayes, Support Vector Machine, Adaboost, Random forest and Neural network were compared and used for classification of skin lesions into ellipse, the most common shape of erythema migrans and erythema migrans class.
%U https://www.sv-jme.eu/sl/article/supervised-visual-system-for-recognition-of-erythema-migrans-an-early-skin-manifestation-of-lyme-borreliosis/
%0 Journal Article
%R 10.5545/sv-jme.2013.1046
%& 115
%P 9
%J Strojniški vestnik - Journal of Mechanical Engineering
%V 60
%N 2
%@ 0039-2480
%8 2018-06-28
%7 2018-06-28
Čuk, Erik, Matjaž  Gams, Matej  Možek, Franc  Strle, Vera  Maraspin Čarman, & Jurij F. Tasič.
"Supervised Visual System for Recognition of Erythema Migrans, an Early Skin Manifestation of Lyme Borreliosis." Strojniški vestnik - Journal of Mechanical Engineering [Online], 60.2 (2014): 115-123. Web.  21 Oct. 2020
TY  - JOUR
AU  - Čuk, Erik 
AU  - Gams, Matjaž 
AU  - Možek, Matej 
AU  - Strle, Franc 
AU  - Maraspin Čarman, Vera 
AU  - Tasič, Jurij F.
PY  - 2014
TI  - Supervised Visual System for Recognition of Erythema Migrans, an Early Skin Manifestation of Lyme Borreliosis
JF  - Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2013.1046
KW  - Lyme borreliosis, erythema migrans, finger draw, segmentation, recognition, attributes
N2  - Lyme borreliosis is the most common human tick-borne infectious disease in the northern hemisphere, occurring predominantly in temperate regions of North America, Europe and Asia. The disease’s most frequent manifestation is erythema migrans, a skin lesion that appears within days to weeks of a tick bite. Early recognition of the lesion is important since it enables proper management and thus prevention of later consequences of the disease which can hamper normal life. In this article, a novel visual system for recognition of erythema migrans is presented based on new technology of smartphones. For detecting erythema migrans edge, we compared three different methods: GrowCut, Maximal Similarity Based Region Merging and Random Walker segmentation method. We have found that the results obtained with GrowCut method are better than those obtained with Random Walker method. Also the GrowCut method, improved with our new figure draw (FD1) marker yields comparable results to those obtained with Maximal Similarity Based Region Merging method. Several classification algorithms Naive Bayes, Support Vector Machine, Adaboost, Random forest and Neural network were compared and used for classification of skin lesions into ellipse, the most common shape of erythema migrans and erythema migrans class.
UR  - https://www.sv-jme.eu/sl/article/supervised-visual-system-for-recognition-of-erythema-migrans-an-early-skin-manifestation-of-lyme-borreliosis/
@article{{sv-jme}{sv-jme.2013.1046},
	author = {Čuk, E., Gams, M., Možek, M., Strle, F., Maraspin Čarman, V., Tasič, J.},
	title = {Supervised Visual System for Recognition of Erythema Migrans, an Early Skin Manifestation of Lyme Borreliosis},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {60},
	number = {2},
	year = {2014},
	doi = {10.5545/sv-jme.2013.1046},
	url = {https://www.sv-jme.eu/sl/article/supervised-visual-system-for-recognition-of-erythema-migrans-an-early-skin-manifestation-of-lyme-borreliosis/}
}
TY  - JOUR
AU  - Čuk, Erik 
AU  - Gams, Matjaž 
AU  - Možek, Matej 
AU  - Strle, Franc 
AU  - Maraspin Čarman, Vera 
AU  - Tasič, Jurij F.
PY  - 2018/06/28
TI  - Supervised Visual System for Recognition of Erythema Migrans, an Early Skin Manifestation of Lyme Borreliosis
JF  - Strojniški vestnik - Journal of Mechanical Engineering; Vol 60, No 2 (2014): Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2013.1046
KW  - Lyme borreliosis, erythema migrans, finger draw, segmentation, recognition, attributes
N2  - Lyme borreliosis is the most common human tick-borne infectious disease in the northern hemisphere, occurring predominantly in temperate regions of North America, Europe and Asia. The disease’s most frequent manifestation is erythema migrans, a skin lesion that appears within days to weeks of a tick bite. Early recognition of the lesion is important since it enables proper management and thus prevention of later consequences of the disease which can hamper normal life. In this article, a novel visual system for recognition of erythema migrans is presented based on new technology of smartphones. For detecting erythema migrans edge, we compared three different methods: GrowCut, Maximal Similarity Based Region Merging and Random Walker segmentation method. We have found that the results obtained with GrowCut method are better than those obtained with Random Walker method. Also the GrowCut method, improved with our new figure draw (FD1) marker yields comparable results to those obtained with Maximal Similarity Based Region Merging method. Several classification algorithms Naive Bayes, Support Vector Machine, Adaboost, Random forest and Neural network were compared and used for classification of skin lesions into ellipse, the most common shape of erythema migrans and erythema migrans class.
UR  - https://www.sv-jme.eu/sl/article/supervised-visual-system-for-recognition-of-erythema-migrans-an-early-skin-manifestation-of-lyme-borreliosis/
Čuk, Erik, Gams, Matjaž, Možek, Matej, Strle, Franc, Maraspin Čarman, Vera, AND Tasič, Jurij.
"Supervised Visual System for Recognition of Erythema Migrans, an Early Skin Manifestation of Lyme Borreliosis" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 60 Number 2 (28 June 2018)

Avtorji

Inštitucije

  • LOTRIČ Metrology, Slovenia 1
  • Institute Jožef Stefan, Department of Intelligent Systems, Slovenia 2
  • University of Ljubljana, Faculty of Electrical Engineering, Slovenia 3
  • University Medical Centre Ljubljana, Department of Infectious Diseases, Slovenia 4

Informacije o papirju

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)2, 115-123

https://doi.org/10.5545/sv-jme.2013.1046

Lyme borreliosis is the most common human tick-borne infectious disease in the northern hemisphere, occurring predominantly in temperate regions of North America, Europe and Asia. The disease’s most frequent manifestation is erythema migrans, a skin lesion that appears within days to weeks of a tick bite. Early recognition of the lesion is important since it enables proper management and thus prevention of later consequences of the disease which can hamper normal life. In this article, a novel visual system for recognition of erythema migrans is presented based on new technology of smartphones. For detecting erythema migrans edge, we compared three different methods: GrowCut, Maximal Similarity Based Region Merging and Random Walker segmentation method. We have found that the results obtained with GrowCut method are better than those obtained with Random Walker method. Also the GrowCut method, improved with our new figure draw (FD1) marker yields comparable results to those obtained with Maximal Similarity Based Region Merging method. Several classification algorithms Naive Bayes, Support Vector Machine, Adaboost, Random forest and Neural network were compared and used for classification of skin lesions into ellipse, the most common shape of erythema migrans and erythema migrans class.

Lyme borreliosis, erythema migrans, finger draw, segmentation, recognition, attributes