Automatic Segmentation of Nasopharyngeal Carcinoma from CT Images:Region Growing Based Technique
This paper describes a framework for automatic nasopharyngeal carcinoma segmentation from CT images. The proposed technique is based on the Region G rowing Method. It is automatic segmentation in which an initial seed is generated without human interventiom The seed is generated from a probabilistic map representing the chances of it being tumor. This map is created from three probabilistic functions based on location of the tumor, intensities, and non-tumor region respectively. The pixel in which the probability is the highest will be selected as potential seeds. Only one representative of these seeds will be selected as an initial seed. Then the seed will be used for region growing subsequently. The experimental results showed that the potential seeds and initial seed were correctly determined with a percentage accuracy of 81.60％ and 95.10％. The seed was grown in preprocessed CT images for identifying the nasopharyngeaJ carcinoma regiom The results showed that, perfect match and corresponding ratio were 71 31％ and 53.00％ respectively.
Automatic Segmentation Nasopharyngeal Carcinoma Region Growing Technique
Chanon Tatanun Panrasee Ritthipravat Thongchai Bhongmakapat LojanaTuntiyatorn
Biomedical Engineering Programme, Faculty of Engineering, Mahidol University,25/25 Puttamolthon 4, S Department of Otolaryngology, Faculty of Medicine, Ramathibodi Hospital, Bangkok, Thailand Department of Radiology, Faculty of Medicine, Ramathibodi Hospital, Bangkok, Thailand
国际会议
2010 2nd International Conference on Signal Processing System(2010年信号处理系统国际会议 ICSPS 2010)
大连
英文
1377-1381
2010-07-05（万方平台首次上网日期，不代表论文的发表时间）