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: 20 dec. 2024. 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. 20 Dec. 2024
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)
Strojniški vestnik - Journal of Mechanical Engineering 60(2014)2, 115-123
© The Authors, CC-BY 4.0 Int. Change in copyright policy from 2022, Jan 1st.
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.