Volume 9, Issue 1 (lasers in medicine 2012)
lmj 2012, 9(1): 6-12 |
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Measurment of Erythema parameter of The PASI standard in psoriasis disease using image processing. lmj 2012; 9 (1) :6-12
URL: http://icml.ir/article-1-241-en.html
URL: http://icml.ir/article-1-241-en.html
Abstract: (11901 Views)
Background: Psoriasis is a skin disease which results in red scaly regions in the body. This disease has no well-known definite cure and the proposed medical treatments can only control the disease and reduce its harms. PASI criteria are proposed to measure the effectiveness of the selected treatment on the patients. The PASI criteria consist of four parameters: Area, Erythema, Scaliness and Thickness. The Erythema parameter is usually measured based on subjective methods by the physicians. Subjective measurement of Erythema is time consuming, imprecise and varies if performed by different physicians. Our objective in this research is to propose an automatic objective method to measure Erythema parameter based on image processing techniques.
Material and Methods: In our research we employed HSV color space because it has the highest correlation with human perception of colors. We specified the correlated component of HSV representation of the psoriasis patients with Erythema parameter. Consequently we used regression modeling to propose a model for automatic measurement of Erythema parameter using HSV color components. We exploited 56 images from psoriasis patients in our research.
Results: The results derived from the proposed method for measurement of Erythema parameter were in accordance with the physicians’ diagnosis in 87% of the cases.
Conclusion: The proposed method can be used as a tool for automatic measurement of Erythema parameter from digital images captured from psoriasis patients. Moreover, The measurement can be performed without need to any special device.
Material and Methods: In our research we employed HSV color space because it has the highest correlation with human perception of colors. We specified the correlated component of HSV representation of the psoriasis patients with Erythema parameter. Consequently we used regression modeling to propose a model for automatic measurement of Erythema parameter using HSV color components. We exploited 56 images from psoriasis patients in our research.
Results: The results derived from the proposed method for measurement of Erythema parameter were in accordance with the physicians’ diagnosis in 87% of the cases.
Conclusion: The proposed method can be used as a tool for automatic measurement of Erythema parameter from digital images captured from psoriasis patients. Moreover, The measurement can be performed without need to any special device.
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