scholarly journals A Method for Tooth Model Reconstruction Based on Integration of Multimodal Images

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Xinwen Zhou ◽  
Yangzhou Gan ◽  
Jing Xiong ◽  
Dongxia Zhang ◽  
Qunfei Zhao ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Orthodontic Treatment ◽  
Ct Images ◽  
Ct Scans ◽  
Reconstruction Method ◽  
Model Reconstruction ◽  
Crown Area ◽  
Computer Aided ◽  
Multimodal Images ◽  
Reconstructed Model

A complete digital tooth model is needed for computer-aided orthodontic treatment. However, current methods mainly use computed tomography (CT) images to reconstruct the tooth model which may require multiple CT scans during orthodontic progress, and the reconstructed model is also inaccurate in crown area. This study developed a tooth model reconstruction method based on integration of CT images and laser scan images to overcome these disadvantages. In the method, crown models and complete tooth models are first reconstructed, respectively, from laser scan images and CT images. Then, crown models from laser scan images and tooth models from CT images are registered. Finally, the crown from laser scan images and root from CT images were fused to obtain a new tooth model. Experimental results verified that the developed method is effective to generate the complete tooth model by integrating CT images and laser scan images. Using the proposed method, the reconstructed models provide more accurate crown than CT images, and it is feasible to obtain complete tooth models at any stage of orthodontic treatment by using one CT scan at the pretreatment stage and one laser scan at that stage to avoid multiple CT scans.

Turbinate atrophy evaluation in pigs by computed tomography

2003 ◽  
Vol 51 (4) ◽  
pp. 485-491 ◽  
Author(s):  
T. Magyar ◽  
F. Kovács ◽  
T. Donkó ◽  
H. Bíró ◽  
R. Romvári ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Nasal Cavity ◽  
Scoring System ◽  
Ct Images ◽  
Area Ratio ◽  
Ct Scans ◽  
Non Invasive ◽  
Visual Scoring ◽  
Ratio Determination ◽  
Visualisation Technique

Computed tomography (CT), a non-invasive visualisation technique was applied for imaging the bony structures of the nasal cavity of pigs, and compared to the traditional scoring system of turbinate atrophy in swine. Twenty-three 27-week-old pigs representing various stages of turbinate atrophy were used. Nasal structures were visually scored on CT scans and transversal cuts of the noses at the level of the first upper premolar teeth using the same scoring system in both cases. A tissue/air area ratio was also determined based on density differences. A highly significant correlation was found between visual scoring of CT images and transversal cuts of pig noses (r = 0.98, p < 0.0001) as well as between visual scoring of CT images and tissue/air area ratio determination (r = -0.82, p < 0.0001).

scholarly journals Gender differences in the maxillary sinus volume : a study using computed tomography scans of a sample of Tamil Nadu population

2016 ◽  
Vol 05 (03) ◽  
pp. 138-142
Author(s):  
N Muthukumaravel ◽  
K. Y. Manjunath
Keyword(s):  
Computed Tomography ◽  
Maxillary Sinus ◽  
Tamil Nadu ◽  
Ct Images ◽  
Ct Scans ◽  
P Value ◽  
Gender Determination ◽  
Maxillary Sinus Volume ◽  
Significant Difference ◽  
Maxillary Sinuses

Abstract Background and aims : Measurements of the maxillary sinus volumes in computed tomography (CT) scans can be used for determination of gender when other methods are inconclusive. Maxillary sinus dimension measurements are valuable in studying sexual dimorphism and can assist in gender determination. The radiographic images can provide adequate measurements for maxillary sinuses that cannot be approached by other means. The purpose of the present study was to determine and compare the volume of the maxillary sinus between males and females of Tamil Nadu region using CT scans. Materials and methods : This study was carried out by using CT images of head region of 100 males and 100 females who underwent CT scanning for indications other than the pathology of the maxillary sinuses. The CT images obtained were of patients between 20 to 50 years of age. The maxillary sinus volume of each side were calculated by using the following formula: Maximal width X Maximal height X Maximal depth X 0.5. Comparison of data between genders and sides was done. The statistical inference was derived by applying unpaired student "t" test and the p value was obtained (p value <.05 was considered statistical significant). Results: Oncomparison of males with females, the mean volumes of maxillary sinuses on each side (left and right) had shown a statistically significant difference (p<.OOOl ). The maxillary sinus volumes of the males were found to be significantly higher than that of the females. Among males, the average mean volume of maxillary sinuses (right + left) is 15.15 ± 0.45 cm3. Among females, the average mean volume of maxillary sinuses (right + left) is 12.77 ± 1.34 em' which is significantly lesser than that of the males. Conclusion : It can be concluded that the volumes of the maxillary sinuses of males are larger than those of the females and this difference is statistically significant. Maxillary sinus dimension measurements can assist in gender determination.

scholarly journals Optimization of a protocol for contrast-enhanced four-dimensional computed tomography imaging of thoracic tumors using minimal contrast agent

2021 ◽  
Author(s):  
Hongya Dai ◽  
Dingqiang Yang ◽  
Lu Chen ◽  
Yibing Zhou ◽  
Xiaojing Wen ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Contrast Agent ◽  
Flow Rate ◽  
Delay Time ◽  
Ct Images ◽  
Ct Scans ◽  
Target Delineation ◽  
4D Ct ◽  
Contrast Enhanced ◽  
Minimal Contrast

Abstract Purpose The accuracy of target delineation for node-positive thoracic tumors is dependent on both four-dimensional computed tomography (4D-CT) and contrast-enhanced three-dimensional (3D)-CT images; these scans enable the motion visualization of tumors and delineate the nodal areas. Combining the two techniques would be more effective; however, currently, there is no standard protocol for the contrast media injection parameters for contrast-enhanced 4D-CT (CE-4D-CT) scans because of its long scan durations and complexity. Thus, we aimed to perform quantitative and qualitative assessments of the image quality of single contrast-enhanced 4D-CT scans to simplify this process and improve the accuracy of target delineation in order to replace the standard clinical modality involved in administering radiotherapy for thoracic tumors. Methods Ninety consecutive patients with thoracic tumors were randomly and parallelly assigned to one of nine subgroups subjected to CE-4D-CT scans with the administration of contrast agent volume equal to the patient’s weight but different flow rate and scan delay time (protocol A1: flow rate of 2.0 ml/s, delay time of 15 s; A2: 2.0 ml/s, 20 s; A3: 2.0 ml/s, 25 s; B1: 2.5 ml/s, 15 s; B2: 2.5 ml/s, 20 s; B3: 2.5 ml/s, 25 s; C1: 3.0 ml/s, 15 s; C2: 3.0 ml/s, 20 s; C3: 3.0 ml/s, 25 s). The Hounsfield unit (HU) values of the thoracic aorta, pulmonary artery stem, pulmonary veins, carotid artery, and jugular vein were acquired for each protocol. Both quantitative and qualitative image analysis and delineation acceptability were assessed. Results The results revealed significant differences among the nine protocols. Enhancement of the vascular structures in mediastinal and perihilar regions was more effective with protocol A1 or A2; however, when interested in the region of superior mediastinum and supraclavicular fossa, protocol C2 or C3 is recommended. Conclusion Qualitatively acceptable enhancement on contrast-enhanced 4D-CT images of thoracic tumors can be obtained by varying the flow rate and delay time when minimal contrast agent is used.

COVID-19 improved diagnoses based on the open-morphology filter and deep-learning

2021 ◽  
Vol 15 ◽  
Author(s):  
Majid Dherar Younus ◽  
Mohammad J M Zedan ◽  
Fahad Layth Malallah ◽  
Mustafa Ghanem Saeed
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Detection Method ◽  
Recognition Rate ◽  
Processing Technique ◽  
Ct Images ◽  
Ct Scans ◽  
Computer Aided ◽  
First Time ◽  
Morphology Filter

Background: Coronavirus (COVID-19) has appeared first time in Wuhan, China, as an acute respiratory syndrome and spread rapidly. It has been declared a pandemic by the WHO. Thus, there is an urgent need to develop an accurate computer-aided method to assist clinicians in identifying COVID-19-infected patients by computed tomography CT images. The contribution of this paper is that it proposes a pre-processing technique that increases the recognition rate compared to the techniques existing in the literature. Methods: The proposed pre-processing technique, which consists of both contrast enhancement and open-morphology filter, is highly effective in decreasing the diagnosis error rate. After carrying out pre-processing, CT images are fed to a 15-layer convolution neural network (CNN) as deep-learning for the training and testing operations. The dataset used in this research has been publically published, in which CT images were collected from hospitals in Sao Paulo, Brazil. This dataset is composed of 2482 CT scans images, which include 1252 CT scans of SARS-CoV-2 infected patients and 1230 CT scans of non-infected SARS-CoV-2 patients. Results: The proposed detection method achieves up to 97.8% accuracy, which outperforms the reported accuracy of the dataset by 97.3%. Conclusion: The performance in terms of accuracy has been improved up to 0.5% by the proposed methodology over the published dataset and its method.

Quantitative Analysis of the Transcondylar Approach to the Foramen Magnum

Neurosurgery ◽  
2001 ◽  
Vol 49 (4) ◽  
pp. 934-943 ◽  
Author(s):  
John E. Wanebo ◽  
Michael R. Chicoine
Keyword(s):  
Computed Tomography ◽  
Quantitative Analysis ◽  
Ct Images ◽  
Foramen Magnum ◽  
Ct Scans ◽  
Computed Tomographic ◽  
Suboccipital Craniotomy ◽  
Before And After ◽  
Skull Measurements ◽  
C 50

Abstract OBJECTIVE Condylar resection with suboccipital craniotomy increases foramen magnum exposure, but guidelines for when this is necessary are not defined. Cadaveric and computed tomography evaluations were completed to guide decision-making regarding the use and extent of condylar resection. METHODS Quantitative analysis of foramen magnum surgical exposures was performed on 32 skulls (64 sides) and 6 cadaveric dissections (12 sides). Computed tomographic (CT) scans were performed on cadaveric heads before and after condylar resections. Digitized images of dry skulls and CT images of cadaver heads were quantitatively analyzed. Predissection CT measurements of cadaveric heads guided extent of condylar resections, and resection accuracy was assessed with postdissection CT scans. RESULTS Skull measurements (means in parentheses) included the foramen magnum area (7.8 cm2), length (3.6 cm), width (3.1 cm), anteroposterior condylar length (2.3 cm), and axial condylar length (2.5 cm). Mean widths of potential surgical exposures for skulls were obtained for A) suboccipital craniotomy (2.3 cm), B) with 25% (2.6 cm), and C) 50% condylar resection (3.0 cm). Mean angles of exposure were as follows: A, 38.4 degrees; B, 49.1 degrees; and C, 54.3 degrees. CT scans of cadaveric heads before and after dissections yielded measurements of exposure equivalent to measurements found on the dry skulls. CONCLUSION On average, lateral exposure increases by 3 mm (13%) and 7 mm (30%) for 25 and 50% condylar resection, respectively, compared with suboccipital craniotomy alone. Angles of exposure increase by 10.7 degrees (28%) and 15.9 degrees (41%). Measurements of CT images can be used preoperatively to help analyze the need for condylar resection and intraoperatively to guide the extent of condylar resection.

DEVELOPMENT OF A SPECIALISED TAPE MEASURE TO ESTIMATE THE SIZE-SPECIFIC DOSE ESTIMATE

2020 ◽  
Vol 191 (3) ◽  
pp. 369-375
Author(s):  
Tomokazu Shohji ◽  
Kazuki Kuriyama ◽  
Nobutaka Yanano ◽  
Yo Katoh
Keyword(s):  
Computed Tomography ◽  
Radiation Dose ◽  
Radiation Exposure ◽  
Ct Images ◽  
Ct Scans ◽  
Dose Estimate ◽  
Ct Examination ◽  
Tape Measure ◽  
Wide Range ◽  
Standard Deviations

Abstract The risk in computed tomography (CT) examinations is radiation exposure. We aimed to develop a specialised tape measure for determining the size-specific dose estimate (SSDE) for patients undergoing CT scans. The scanning parameters used were those of the abdominal protocol in our institute. With this method, the SSDE220 and standard deviations obtained from CT images for the liver, pelvic and lung areas, corresponded closely to the SSDEtape and standard deviations obtained using the tape measure. We thus devised a new idea that allows the estimation of the SSDE220 using a specialised tape measure before the CT examination, allowing for an informed explanation of the radiation dose to the patient. Although the tape measure developed in this study is specific to one particular CT instrument, the method could be adapted to a wide range of radiography applications.

scholarly journals Tailoring steroids in the treatment of COVID-19 pneumonia assisted by CT scans: three case reports

2020 ◽  
Vol 28 (5) ◽  
pp. 885-892 ◽  
Author(s):  
Ying Su ◽  
Yi Han ◽  
Jie Liu ◽  
Yue Qiu ◽  
Qian Tan ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Computed Tomography ◽  
Quantitative Analysis ◽  
Disease Severity ◽  
Initial Treatment ◽  
Case Reports ◽  
Ct Images ◽  
Ct Scans ◽  
Serial Ct ◽  
Analysis Of The Images

In this article, we analyze and report cases of three patients who were admitted to Renmin Hospital, Wuhan University, China, for treating COVID-19 pneumonia in February 2020 and were unresponsive to initial treatment of steroids. They were then received titrated steroids treatment based on the assessment of computed tomography (CT) images augmented and analyzed with the artificial intelligence (AI) tool and output. Three patients were finally recovered and discharged. The result indicated that sufficient steroids may be effective in treating the COVID-19 patients after frequent evaluation and timely adjustment according to the disease severity assessed based on the quantitative analysis of the images of serial CT scans.

scholarly journals Factors affecting incorrect interpretation of abdominal computed tomography in non-traumatic patients by novice emergency physicians

2021 ◽  
Vol 8 (3) ◽  
pp. 207-215
Author(s):  
Seong Geun Lee ◽  
Hanjin Cho ◽  
Joo Yeong Kim ◽  
Juhyun Song ◽  
Jong-Hak Park
Keyword(s):  
Computed Tomography ◽  
Confidence Interval ◽  
Biliary Tract ◽  
Biliary Tract Disease ◽  
Ct Images ◽  
Ct Scans ◽  
Urinary System ◽  
Abdominal Ct ◽  
Factors Associated ◽  
Tract Disease

Objective Accurate interpretation of computed tomography (CT) scans is critical for patient care in the emergency department. We aimed to identify factors associated with an incorrect interpretation of abdominal CT by novice emergency residents and to analyze the characteristics of incorrectly interpreted scans.Methods This retrospective analysis of a prospective observational cohort was conducted at three urban emergency departments. Discrepancies between the interpretations by postgraduate year-1 (PGY-1) emergency residents and the final radiologists’ reports were assessed by independent adjudicators. Potential factors associated with incorrect interpretation included patient age, sex, time of interpretation, and organ category. Adjusted odds ratios (aORs) for incorrect interpretation were calculated using multivariable logistic regression analysis.Results Among 1,628 eligible cases, 270 (16.6%) were incorrect. The urinary system was the most correctly interpreted organ system (95.8%, 365/381), while the biliary tract was the most incorrectly interpreted (28.4%, 48/169). Normal CT images showed high false-positive rates of incorrect interpretation (28.2%, 96/340). Organ category was found to be a major determinant of incorrect interpretation. Using the urinary system as a reference, the aOR for incorrect interpretation of biliary tract disease was 9.20 (95% confidence interval, 5.0–16.90) and the aOR for incorrectly interpreting normal CT images was 8.47 (95% confidence interval, 4.85–14.78).Conclusion Biliary tract disease is a major factor associated with incorrect preliminary interpretations of abdominal CT scans by PGY-1 emergency residents. PGY-1 residents also showed high false-positive interpretation rates for normal CT images. Emergency residents’ training should focus on these two areas to improve abdominal CT interpretation accuracy.

Adaptive Surface Mesh Reconstruction for Computed Tomography Images

2019 ◽  
Vol 9 (6) ◽  
pp. 1086-1094 ◽  
Author(s):  
Zhong Chen ◽  
Zhiwei Hou ◽  
Mujian Xia ◽  
Yuegang Xing
Keyword(s):  
Computed Tomography ◽  
Cervical Vertebrae ◽  
Lumbar Vertebrae ◽  
Biological Tissues ◽  
Ct Images ◽  
Reconstruction Method ◽  
Surface Mesh ◽  
Computed Tomography Images ◽  
Surface Meshes ◽  
Mesh Reconstruction

In medical applications, it is important to reconstruct surface meshes from Computed Tomography (CT) images. Surface mesh reconstruction of biological tissues actually suffers from staircase artifacts, due to anisotropic CT data. To solve this problem, this paper proposes an adaptive surface mesh reconstruction method. We convert the contour pixels of medical image to contour points and exploit the adaptive spherical cover to produce an approximating surface based on the contour points. Due to the reconstruction quality depending on the accurate normal estimation, computing the normal vectors from the negative gradient based on 3D binary volume data instead of classical principal component analysis (PCA), and then covering contour points by adaptive spheres, linking the auxiliary points in the spheres for reconstructing adaptive triangular meshes. The presented method has been used in CT images of the first cervical vertebrae (C1), scapula, as well as the third lumbar vertebrae (L3) and the results are analyzed regarding their smoothness, accuracy and mesh quality. The results show that our method can reconstruct smooth, accurate and high-quality adaptive surface meshes.

A Radiologist's Art in CT Images

2013 ◽  
Vol 3 (4) ◽  
pp. 61-66
Author(s):  
Piyu Deo Mahant
Keyword(s):  
Computed Tomography ◽  
Medical Imaging ◽  
Human Body ◽  
Ct Images ◽  
Ct Scans ◽  
X Rays ◽  
Imaging Studies ◽  
X Ray ◽  
X Ray Computed

The story of medical imaging starts on 8 Nov, 1895, when Wilhelm Conrad Röntgen accidentally discovered X rays. Since then it has undergone great technological advancements helping physicians create images of the human body to reveal, diagnose, or examine disease (X-ray, n.d). CT scans combine the use of computers and x-rays to create virtual 'slices' of what is inside our body without cutting it open. Earlier many diseases could only be confirmed at autopsy. In 2010, more than 5 billion medical imaging studies were completed done worldwide (X-ray computed tomography, n.d).

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