DocumentCode :
2570761
Title :
The segmentation algorithm of dental CT images based on fuzzy maximum entropy and region growing
Author :
Dong-Ri, Shan ; Fu-Yuan, Gao
Author_Institution :
Sch. of Mech. Eng., Shandong Inst. of Light Ind., Jinan, China
fYear :
2010
fDate :
16-18 April 2010
Firstpage :
74
Lastpage :
78
Abstract :
Because the dental structure is irregular and particular, an automatic segmentation algorithm is proposed, which is based on fuzzy maximum entropy theory and region growing method. It achieves automatic acquisition of thresholds and seeds, and gets an accurate segmentation results. With the help of ICM algorithm, it resolves the problem of excessive calculation in the process of automatic threshold acquisition. The applications prove that the new algorithm is intuitive, simple, robust and easy to implement.
Keywords :
computerised tomography; data acquisition; dentistry; image segmentation; maximum entropy methods; medical image processing; automatic segmentation algorithm; automatic threshold acquisition; dental CT images; dental structure; fuzzy maximum entropy theory; image segmentation; region growing method; Accelerometers; Biomedical monitoring; Computed tomography; Dentistry; Entropy; Image segmentation; Real time systems; Sensor systems; Thigh; Wearable sensors; ICM algorithm; fuzzy maximum entropy; region growing; thresholding segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedical Technology (ICBBT), 2010 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6775-4
Type :
conf
DOI :
10.1109/ICBBT.2010.5479006
Filename :
5479006
Link To Document :
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