3D Region Merging for Segmentation of Teeth on Cone-Beam Computed Tomography Images

被引：5

作者：

Indraswari, Rarasmaya ^{[1
]}

Kurita, Takio ^{[2
]}

Arifin, Agus Zainal ^{[1
]}

Suciati, Nanik ^{[1
]}

Astuti, Eha Renwi ^{[3
]}

Navastara, Dini Adni ^{[1
]}

机构：

[1] Inst Teknol Sepuluh Nopember, Dept Informat, Surabaya, Indonesia

[2] Hiroshima Univ, Dept Informat Engn, Hiroshima, Japan

[3] Univ Airlangga, Fac Med Dent, Surabaya, Indonesia

来源：

2018 JOINT 10TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS (SCIS) AND 19TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS (ISIS) | 2018年

关键词：

cone-beam computed tomography; region merging; teeth segmentation; three-dimensional image; CT;

D O I：

10.1109/SCIS-ISIS.2018.00065

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Segmentation of teeth in Cone-Beam Computed Tomography (CBCT) images is challenging problem due to its noise and the similar grayscale intensity of bone and teeth element. In this paper we proposed a new method based on three-dimensional (3D) region merging and histogram thresholding for automatic segmentation of teeth on CBCT images. The proposed 3D region merging algorithm can recognized the teeth element that have similar intensity with the bone element based on the three-dimensional (3D) information of the neighboring slices of the CBCT image. Merging the teeth region will lead to more homogenous grayscale intensity distribution inside the teeth. Then histogram thresholding that utilized the characteristic of CBCT images is performed to binarize the grayscale images and obtain the teeth object. The average accuracy, sensitivity, and specificity of the proposed method are 97.75%, 80.22%, and 98.31%, respectively. The proposed method is fully automatic, therefore lead to more objective and reproducible results.

引用

页码：341 / 345

页数：5

共 9 条

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