Abstract
Past statistics have revealed that breast cancer is the world’s leading cause of death among women. One popular method of screening breast cancer is ultrasound. However, reading an ultrasound image is not an easy task because it lacks spatial resolution, subject to image distortion, susceptible to noise and is highly operator dependant. Several image processing techniques have been introduced to enhance the detection of diagnostic features. This study proposes modified seed based region growing algorithm to detect the edges and segment the area of solid masses in an ultrasound image without having to specify the location of the seed and the grey level threshold value manually. Automatic seed selection is done by using moving k-means clustering. A performance analysis has been carried out towards 3 different ultrasound images. The results reveal that this algorithm can detect the edges of solid masses and segment it from the rest of the image effectively.
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Isa, N.A.M., Sabarudin, S., Ngah, U.K., Zamli, K.Z. (2005). Automatic Detection of Breast Tumours from Ultrasound Images Using the Modified Seed Based Region Growing Technique. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552451_19
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DOI: https://doi.org/10.1007/11552451_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28895-4
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