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