JICCE (한국정보통신학회)
Current Result Document : 5 / 5
| 한글제목(Korean Title) |
Ganglion Cyst Region Extraction from Ultrasound lmages Using Possibilistic C-Means Clustering Method |
| 영문제목(English Title) |
Ganglion Cyst Region Extraction from Ultrasound lmages Using Possibilistic C-Means Clustering Method |
| 저자(Author) |
Alethea Suryadibrata
Kwang Baek Kim
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| 원문수록처(Citation) |
VOL 15 NO. 01 PP. 0049 ~ 0052 (2017. 03) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Ganglion cysts are benign soft tissues usually encountered in the wrist. In this paper, we propose a method to extract a ganglion cyst region from ultrasonography images by using image segmentation. The proposed method using the possibilistic c-means (PCM) clustering method is applicable to ganglion cyst extraction. The methods considered in this thesis are fuzzy stretching median filter PCM clustering, and connected component labeling. Fuzzy stretching performs well on and improves the original image. Median filter reduces the speckle noise without decreasing the ultrasonography images image sharpness. PCM clustering is used for categorizing pixels into the given cluster centers. Connected component labeling is used for labeling the objects in an image and extracting the cyst region. Further, PCM clustering is more robust in the case of noisy data, and the proposed method can extract a ganglion cyst area with an accuracy of 80% (16 out of 20 images)
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| 키워드(Keyword) |
Clustering
Cyst
Fuzzy stretching
Possibilistic c-means
Ultrasonography
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| 파일첨부 |
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