An Efficient Segmentation Technique for Different Medical Image Modalities | ||||
| Menoufia Journal of Electronic Engineering Research | ||||
| Article 3, Volume 30, Issue 1, January 2021, Page 22-28 PDF (1011.94 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/mjeer.2021.146077 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Amira A. Mahmoud; Walid El-Shafai ; Taha E. Taha; El-Sayed El-Rabaie; Osama Zahran; Adel El-Fishawy; Fathi E. Abd El-Samie
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| Depart. of Electronics and Electrical Comm., Faculty of Electronic Eng., Menoufia Uni., Egypt. | ||||
| Abstract | ||||
| In this paper, a study of the segmentation of medical images is presented. The paper provides a solid introduction to image enhancement along with image segmentation fundamentals. Firstly, the local spatial information of the image is enhanced with morphological operations to ensure noise-immunity and image detail-protection. The objective of using morphological operations is to remove the defects in the texture of the image. Secondly, fuzzy c-means (FCM) clustering is used with modification of membership function based only on the spatial neighbors instead of the distance between pixels within local spatial neighbors and cluster centers. The proposed technique is very simple to implement and significantly fast, since it is not necessary to compute the distance between the neighboring pixels and the cluster centers. It is also efficient when dealing with noisy images because of its ability to improve membership partition matrix efficiently. Experimental results performed on different medical image modalities illustrate that the proposed technique can achieve good results, as well as short time and efficient image segmentation. | ||||
| Keywords | ||||
| Image segmentation; Ultrasonic; X-ray; CT; PET; MR; FCM; Morphological operations; Active contour | ||||
| References | ||||
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