TH-D-332-04: Automatic Registration Technique for Rotating-Gantry Dual-Detector Region-Of-Interest Cone-Beam Computed Tomography (ROI-CBCT)

2008 ◽  
Vol 35 (6Part27) ◽  
pp. 2991-2991
Author(s):  
V Patel ◽  
K Hoffmann ◽  
D Bednarek ◽  
S Rudin
Keyword(s):  
Computed Tomography ◽  
Cone Beam Computed Tomography ◽  
Region Of Interest ◽  
Cone Beam ◽  
Automatic Registration ◽  
Dual Detector

scholarly journals Region-of-interest cone beam computed tomography (ROI CBCT) with a high resolution CMOS detector

2015 ◽  
Author(s):  
A. Jain ◽  
H. Takemoto ◽  
M. D. Silver ◽  
S. V. S. Nagesh ◽  
C. N. Ionita ◽  
...  
Keyword(s):  
Computed Tomography ◽  
High Resolution ◽  
Cone Beam Computed Tomography ◽  
Region Of Interest ◽  
Cone Beam

scholarly journals Research on Panoramic Stitching Algorithm of Lateral Cranial Sequence Images in Dental Multifunctional Cone Beam Computed Tomography

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2200
Author(s):  
Junyuan Liu ◽  
Xi Li ◽  
Siwan Shen ◽  
Xiaoming Jiang ◽  
Wang Chen ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Cone Beam Computed Tomography ◽  
Region Of Interest ◽  
Gaussian Mixture ◽  
Block Matching ◽  
Cone Beam ◽  
Fusion Algorithm ◽  
Panoramic Images

In the design of dental multifunctional Cone Beam Computed Tomography, the linear scanning strategy not only saves equipment cost, but also avoids the demand for patients to be repositioned when acquiring lateral cranial sequence images. In order to obtain panoramic images, we propose a local normalized cross-correlation stitching algorithm based on Gaussian Mixture Model. Firstly, the Block-Matching and 3D filtering algorithm is used to remove quantum and impulse noises according to the characteristics of X-ray images; Then, the segmentation of the irrelevant region and the extraction of the region of interest are performed by Gaussian Mixture Model; The locally normalized cross-relation is used to complete the registration with the multi-resolution strategy based on wavelet transform and Particle Swarm Optimization algorithm; Finally, image fusion is achieved by the weighted smoothing fusion algorithm. The experimental results show that the panoramic image obtained by this method has significant performance in both subjective vision and objective quality evaluation and can be applied to preoperative diagnosis of clinical dental deformity and postoperative effect evaluation.

scholarly journals Automatic Segmentation of Dental Cone Beam Computed Tomography Image Based on Level Set Method Using Morphology Operators and Polynomial Fitting

2020 ◽  
Vol 4 (1) ◽  
pp. 45-52
Author(s):  
Fahmi Syuhada Syuhada ◽  
Agus Zainal Arifin
Keyword(s):  
Computed Tomography ◽  
Level Set ◽  
Cone Beam Computed Tomography ◽  
Automatic Segmentation ◽  
Region Of Interest ◽  
Ground Truth ◽  
Cone Beam ◽  
Polynomial Fitting ◽  
Analysis Process ◽  
Computed Tomography Image

Abstract Automatic Segmentation of dental cone beam computed tomography (CBCT) images is challenging due to the intensity of the teeth that have low level intensity. In this paper we proposes a new method for automatic teeth segmentation in slices of CBCT images based on level let method using morphology operators and polynomial fitting. Morphology operators are used to construct the Region of Interest (ROI) area of dental objects in the image slice. ROI is used to focus the analysis process on areas of dental objects which generally have a polynomial pattern distribution. Polynomial fitting is obtained to estimation arc of teeth structure in CBCT images. Level Set is implemented to evolve the ROI to obtain the contours of dental objects. Comparison between proposed method result and the ground truth images shows that the method gives best average accuracy, sensitivity, and specificity value of 99.02%, 95.32%, 99.09%, respectively. This value that the proposed method is promising for accurate segmentation of the entire tooth form on CBCT images.

Value of cone beam computed tomography to evaluate complication of intracranial haemorrhage in endovascular treatment (evt): a case report

2019 ◽  
Vol 1 (1) ◽  
pp. 16-18 ◽  
Author(s):  
Norafida Bahari ◽  
Nik Azuan Nik Ismail ◽  
Jegan Thanabalan ◽  
Ahmad Sobri Muda
Keyword(s):  
Computed Tomography ◽  
Arteriovenous Malformation ◽  
Endovascular Treatment ◽  
Cone Beam Computed Tomography ◽  
Diagnostic Value ◽  
Cone Beam ◽  
Brain Arteriovenous Malformation ◽  
Embolic Materials

In this article, we evaluate the effectiveness of Cone Beam Computed Tomography, through a case study, in assessing the complication of intracranial bleeding during an endovascular treatment of brain arteriovenous malformation when compared to Multislice-Detector Computed Tomography performed immediately after the procedure. The image quality of Cone Beam Computed Tomography has enough diagnostic value in differentiating between haemorrhage, embolic materials and the arteriovenous malformation nidus to facilitate physicians to decide for further management of the patient.

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