Mammary Gland Tumor Detection in Cats Using Ant Colony Optimisation

Citation:
Hossam Moftah, Walaa Elmasry, M. Ibrahiem, A. E. Hassanien, and G. Schaefer, "Mammary Gland Tumor Detection in Cats Using Ant Colony Optimisation", 2nd IAPR Asian Conference on Pattern Recognition (ACPR), pp.942- 945, Okinawa, Japan. , 5 Nov., 2013.

Date Presented:

5 Nov.

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Mammary gland tumors are among the most common tumors in cats. Over 85 percent of mammary tumors in cats are malignant and they tend to grow and metastasize quickly to different organs like lungs and lymph nodes. Similar to breast tumors in humans, they start as a small lump in a mammary gland and then grow and increase in size unless detected and treated. In this paper, we present an approach to detect broadenoma mammary gland tumors in cats using ant colony optimisation. Image features can then be extracted from the segmented image regions. To evaluate the performance of our presented approach, 25 microscopical images were taken from tissue slides of broadenomas from three cat cases. The experimental results obtained confirm that the effectiveness and performance of the proposed system is high.

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