Volume 8, Issue 2 (laser medicine journal 2011)
lmj 2011, 8(2): 20-26 |
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Using Edge Detection Method for Lesion Area Assessment in PASI. lmj 2011; 8 (2) :20-26
URL: http://icml.ir/article-1-225-en.html
URL: http://icml.ir/article-1-225-en.html
Abstract: (15221 Views)
Background: Psoriasis is a skin disease which has genetical origin. In this disease, skin is covered by red plaques and silvery-white scales. PASI standard provides a method for measuring psoriasis severity by evaluating lesion area and three other parameters.
Material and Methods: To determine the lesion area on the skin, we have developed an automatic method for segmentation of the plaques. The method isolates healthy and healed skin areas from lesion areas by an edge detection method. We customized the canny edge detection method in CIELAB color space to isolate the plaques from skin.
Result: Moreover the simulation results indicate that the proposed method is able to determine lesion areas with accuracy higher than 92 percent for 37 out of 40 cases.
Conclusion: The advantage of this method is that it can find lesion area in noisy body, face and can remove the hair, eyes and mouth artifacts. Hence, the proposed method is superior to the previous methods and can be effectively used in automatic measuring of the lesion area in psoriasis patients.
Material and Methods: To determine the lesion area on the skin, we have developed an automatic method for segmentation of the plaques. The method isolates healthy and healed skin areas from lesion areas by an edge detection method. We customized the canny edge detection method in CIELAB color space to isolate the plaques from skin.
Result: Moreover the simulation results indicate that the proposed method is able to determine lesion areas with accuracy higher than 92 percent for 37 out of 40 cases.
Conclusion: The advantage of this method is that it can find lesion area in noisy body, face and can remove the hair, eyes and mouth artifacts. Hence, the proposed method is superior to the previous methods and can be effectively used in automatic measuring of the lesion area in psoriasis patients.
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