AUTOMATIC SEGMENTATION FOR 3D DENTAL RECONSTRUCTION

被引：0

作者：

Pavaloiu, Ionel-Bujorel ^{[1
]}

Goga, Nicolae ^{[1
]}

Marin, Iuliana ^{[1
]}

Vasilateanu, Andrei ^{[1
]}

机构：

[1] Univ Politehn Bucuresti, Bucharest, Romania

来源：

2015 6TH INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION AND NETWORKING TECHNOLOGIES (ICCCNT) | 2015年

关键词：

Image Segmentation; Cone Beam Computer Tomography; Dentistry; Canny edge detector; CONE-BEAM CT; TOOTH; MODELS;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Cone Beam Computed Tomography (CBCT) is one of the favorite imaging technologies in dentistry because if offers 3D images in conditions of reduced irradiation. High quality 3D imaging is essential for first-rate diagnostic and treatment, despite the rather low quality images, with low contrast and high noise. The paper presents an automatic method for 3D reconstruction of the oral cavity. We analyze the existing state of the art in the field and propose a segmentation method that uses the domain knowledge related to mouth and teeth to reduce the computational load and to provide good results in an automatic procedure. The method is based on a Canny type edge detector, that was found to offer better control than active contour methods.

引用

页码：216 / 221

页数：6

共 50 条

[21] 3D automatic levels propagation approach to breast MRI tumor segmentation
Bouchebbah, Fatah
Slimani, Hachem
EXPERT SYSTEMS WITH APPLICATIONS, 2021, 165
[22] 3D Model Reconstruction based on Plantar Image's Feature Segmentation
Zhang, Maqiu
Zhang, Zhenning
Li, Weiqing
PROCEEDINGS OF 2017 IEEE INTERNATIONAL CONFERENCE ON PROGRESS IN INFORMATICS AND COMPUTING (PIC 2017), 2017, : 164 - 168
[23] Automatic Segmentation of Antenatal 3-D Ultrasound Images
Anquez, Jeremie
Angelini, Elsa D.
Grange, Gilles
Bloch, Isabelle
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2013, 60 (05) : 1388 - 1400
[24] Development and evaluation of a semi-automatic 3D segmentation technique of the carotid arteries from 3D ultrasound images
Gill, JD
Ladak, HM
Steinman, DA
Fenster, A
MEDICAL IMAGING 1999: IMAGE PROCESSING, PTS 1 AND 2, 1999, 3661 : 214 - 221
[25] Low-dose Liver CT Images Segmentation and 3D Reconstruction
Liu, Fan
Jin, Xinyu
Qiu, Wenyuan
Li, Lanjuan
PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON ELECTROMECHANICAL CONTROL TECHNOLOGY AND TRANSPORTATION, 2015, 41 : 309 - 313
[26] Automatic 3D Reconstruction from Multi-Date Satellite Images
Facciolo, Gabriele
de Franchis, Carlo
Meinhardt-Llopis, Enric
2017 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW), 2017, : 1542 - 1551
[27] Automatic forensic identification using 3D sphenoid sinus segmentation and deep characterization
Souadih, Kamal
Belaid, Ahror
Ben Salem, Douraied
Conze, Pierre-Henri
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, 2020, 58 (02) : 291 - 306
[28] Combining a deformable model and a probabilistic framework for an automatic 3D segmentation of prostate on MRI
Makni, Nasr
Puech, P.
Lopes, R.
Dewalle, A. S.
Colot, O.
Betrouni, N.
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY, 2009, 4 (02) : 181 - 188
[29] Current methods in the automatic tissue segmentation of 3D magnetic resonance brain images
Liew, AWC
Yan, H
CURRENT MEDICAL IMAGING, 2006, 2 (01) : 91 - 103
[30] Semi-automatic segmentation for 3D motion analysis of the tongue with dynamic MRI
Lee, Junghoon
Woo, Jonghye
Xing, Fangxu
Murano, Emi Z.
Stone, Maureen
Prince, Jerry L.
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, 2014, 38 (08) : 714 - 724

← 1 2 3 4 5 →