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This paper presents an optimized normalized cut method for segmentation of RBCs infected with malarial parasites using peripheral blood smears. The algorithm is applied over various color spaces to find its optimal performance for microscopic blood smear images. We tested the efficacy of results in RGB, YCbCr, HSV and NTSC using the Rand's Index. The work is useful in telepathology applications and can automate the screening of malaria in rural areas where healthcare manpower is limited.