Abstract
This chapter presents a novel method for segmentation of normal and noisy MRI medical images. In the proposed algorithm, Genetic Algorithm-based FCM-S1 (GAFCM-S1) is used which takes into consideration the effect of the neighborhood pixels around a central pixel and exploits this property for noise reduction. While spatial FCM (SFCM) also considers this feature, this method is still preferable over the others as it is a relatively faster method. Moreover, GAFCM-S1 is self-starting and the centroids are completely independent of the user inputs. Turi’s Validity Index has been used as a measure of proper segmentation.
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Halder, A., Maity, A., Sarkar, A., Das, A. (2019). A Dynamic Spatial Fuzzy C-Means Clustering-Based Medical Image Segmentation. In: Abraham, A., Dutta, P., Mandal, J., Bhattacharya, A., Dutta, S. (eds) Emerging Technologies in Data Mining and Information Security. Advances in Intelligent Systems and Computing, vol 813. Springer, Singapore. https://doi.org/10.1007/978-981-13-1498-8_73
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