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Tumor Detection Algorithm Using Boundary Based Approach


Affiliations
1 Rungta College of Engineering and Technology, Bhilai, Chhattisgarh, India
     

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Boundary detection has been recognized as one of the difficult problems in image processing and pattern analysis, in particular in medical imaging applications. There is no unified approach to this problem, which has been found to be application dependent. In this paper, we present a simple and yet effective method to find the borders of tumors as an initial step towards the diagnosis of skin tumors from their color images. The method makes use of an adaptive color metric from the red, green, and blue (RGB) planes that contain information to discriminate the tumor from the background. Using this suitable coordinate transformation, the image is segmented. The tumor portion is then extracted from the segmented image and borders are drawn. Experimental results that verify the effectiveness of this approach are given.

Keywords

Tumor, Cell, Primary, Secondary, SOL, Clustering, Knowledge, Boundary.
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  • Tumor Detection Algorithm Using Boundary Based Approach

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Authors

Rakesh Kumar Soni
Rungta College of Engineering and Technology, Bhilai, Chhattisgarh, India
Shrikant B. Burje
Rungta College of Engineering and Technology, Bhilai, Chhattisgarh, India

Abstract


Boundary detection has been recognized as one of the difficult problems in image processing and pattern analysis, in particular in medical imaging applications. There is no unified approach to this problem, which has been found to be application dependent. In this paper, we present a simple and yet effective method to find the borders of tumors as an initial step towards the diagnosis of skin tumors from their color images. The method makes use of an adaptive color metric from the red, green, and blue (RGB) planes that contain information to discriminate the tumor from the background. Using this suitable coordinate transformation, the image is segmented. The tumor portion is then extracted from the segmented image and borders are drawn. Experimental results that verify the effectiveness of this approach are given.

Keywords


Tumor, Cell, Primary, Secondary, SOL, Clustering, Knowledge, Boundary.