scholarly journals Age Estimation from Computed Tomography of Cranial Suture Closure in a Thai Population

2020 ◽  
Vol 15 (2) ◽  
pp. 276-289
Author(s):  
Pasuk Mahakkanukrauh ◽  
Keyword(s):  
Computed Tomography ◽  
Age Estimation ◽  
Ct Images ◽  
Ct Image ◽  
Cranial Suture ◽  
Thai Population ◽  
Age Related ◽  
Fundamental Information ◽  
Starting Point ◽  
Suture Closure

Age estimation from human skeletal remains is an important step to reconstruct a biological profile. Cranial suture has long been studied for its age-related closure. However, until now, forensic anthropologists still attempt to investigate the best way of estimating age at death from cranial suture closure because skull is usually found at the crime scene due to its easy recognised-appearance and persistence to post-mortem insults. For these reasons, a study of age estimation from cranial suture closure in a Thai population was conducted, which focussed to study the appearance and visibility of facial suture closure using computed tomography (CT). CT image series of 140 cases were obtained in order to investigate ectocranial closure of the selected facial sutures. The results from CT image analysis revealed that nasomaxillary provided the most consistent examination of suture closure (52%) while frontonasal delivered the lowest consistency in suture closure examination (29%). The inconsistency mostly occurred in assigning the closure score of 1 and 2. Thus, it could be suggested that a 3-scale scoring system of closure: open, closing, and closed, could be an appropriate method of evaluating degree of ectocranial closure of facial sutures obtained from CT imaging. This fundamental information of facial suture closure from CT images could serve as a starting point on development of age estimation technique from suture closure by utilising CT images.

Age estimation approaches using cranial suture closure: A validation study on a Thai population

2018 ◽  
Vol 53 ◽  
pp. 79-86 ◽  
Author(s):  
Sittiporn Ruengdit ◽  
Sukon Prasitwattanaseree ◽  
Karnda Mekjaidee ◽  
Apichat Sinthubua ◽  
Pasuk Mahakkanukrauh
Keyword(s):  
Validation Study ◽  
Age Estimation ◽  
Cranial Suture ◽  
Thai Population ◽  
Suture Closure

scholarly journals Multi-Cycle-Consistent Adversarial Networks for Edge Denoising of Computed Tomography Images

2021 ◽  
Vol 17 (4) ◽  
pp. 1-16
Author(s):  
Xiaowe Xu ◽  
Jiawei Zhang ◽  
Jinglan Liu ◽  
Yukun Ding ◽  
Tianchen Wang ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Image Denoising ◽  
Ct Images ◽  
High Dose ◽  
Ct Image ◽  
Paired Data ◽  
High Quality ◽  
Computed Tomography Images ◽  
Significant Difference ◽  
Global Cycle

As one of the most commonly ordered imaging tests, the computed tomography (CT) scan comes with inevitable radiation exposure that increases cancer risk to patients. However, CT image quality is directly related to radiation dose, and thus it is desirable to obtain high-quality CT images with as little dose as possible. CT image denoising tries to obtain high-dose-like high-quality CT images (domain Y ) from low dose low-quality CT images (domain X ), which can be treated as an image-to-image translation task where the goal is to learn the transform between a source domain X (noisy images) and a target domain Y (clean images). Recently, the cycle-consistent adversarial denoising network (CCADN) has achieved state-of-the-art results by enforcing cycle-consistent loss without the need of paired training data, since the paired data is hard to collect due to patients’ interests and cardiac motion. However, out of concerns on patients’ privacy and data security, protocols typically require clinics to perform medical image processing tasks including CT image denoising locally (i.e., edge denoising). Therefore, the network models need to achieve high performance under various computation resource constraints including memory and performance. Our detailed analysis of CCADN raises a number of interesting questions that point to potential ways to further improve its performance using the same or even fewer computation resources. For example, if the noise is large leading to a significant difference between domain X and domain Y , can we bridge X and Y with a intermediate domain Z such that both the denoising process between X and Z and that between Z and Y are easier to learn? As such intermediate domains lead to multiple cycles, how do we best enforce cycle- consistency? Driven by these questions, we propose a multi-cycle-consistent adversarial network (MCCAN) that builds intermediate domains and enforces both local and global cycle-consistency for edge denoising of CT images. The global cycle-consistency couples all generators together to model the whole denoising process, whereas the local cycle-consistency imposes effective supervision on the process between adjacent domains. Experiments show that both local and global cycle-consistency are important for the success of MCCAN, which outperforms CCADN in terms of denoising quality with slightly less computation resource consumption.

scholarly journals The Impact of Sex and Ancestry on Cranial Sutures in the Hamann Todd Collection

2014 ◽  
Vol 22 ◽  
pp. 68-80
Author(s):  
Rajitha Sivakumaran
Keyword(s):  
Age Estimation ◽  
Population Based ◽  
Cranial Sutures ◽  
Cranial Suture ◽  
Suture Closure ◽  
Unreliable Method ◽  
The Impact

Cranial suture closure has been regarded as an unreliable method for age estimation due to the large amount ofvariability in the commencement, progression and termination of fusion. The Hamann Todd Osteological Collectionwas used to examine the sagittal, coronal and lambdoid sutures in an attempt to determine the impact of sex and ancestry on synostosis. The sagittal does not appear to be impacted by sex, but in the coronal and lambdoid sutures,significant sex-based differences were noted. Generally, females exhibited greater progression than males, butsynostosis was more strongly related to age in males. Stronger age-score correlations were present in black individuals compared to white individuals. This questions the application of current cranial aging methods, which do not address sex- and population-based differences in the commencement, progression and termination ofsutural fusion.

scholarly journals Chest CT Images for COVID-19: Radiologists and Computer-based detection

2020 ◽  
Author(s):  
Qingli Dou ◽  
Jiangping Liu ◽  
Wenwu Zhang ◽  
Yanan Gu ◽  
Wan-Ting Hsu ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Image Analysis ◽  
Ct Images ◽  
Chest Ct ◽  
Image Analysis System ◽  
Ct Image ◽  
Chest Computed Tomography ◽  
Computer Based ◽  
Analysis System ◽  
Novel Coronavirus

ABSTRACTBackgroundCharacteristic chest computed tomography (CT) manifestation of 2019 novel coronavirus (COVID-19) was added as a diagnostic criterion in the Chinese National COVID-19 management guideline. Whether the characteristic findings of Chest CT could differentiate confirmed COVID-19 cases from other positive nucleic acid test (NAT)-negative patients has not been rigorously evaluated.PurposeWe aim to test whether chest computed tomography (CT) manifestation of 2019 novel coronavirus (COVID-19) can be differentiated by a radiologist or a computer-based CT image analysis system.MethodsWe conducted a retrospective case-control study that included 52 laboratory-confirmed COVID-19 patients and 80 non-COVID-19 viral pneumonia patients between 20 December, 2019 and 10 February, 2020. The chest CT images were evaluated by radiologists in a double blind fashion. A computer-based image analysis system (uAI system, Lianying Inc., Shanghai, China) detected the lesions in 18 lung segments defined by Boyden classification system and calculated the infected volume in each segment. The number and volume of lesions detected by radiologist and computer system was compared with Chi-square test or Mann-Whitney U test as appropriate.ResultsThe main CT manifestations of COVID-19 were multi-lobar/segmental peripheral ground-glass opacities and patchy air space infiltrates. The case and control groups were similar in demographics, comorbidity, and clinical manifestations. There was no significant difference in eight radiologist identified CT image features between the two groups of patients. There was also no difference in the absolute and relative volume of infected regions in each lung segment.ConclusionsWe documented the non-differentiating nature of initial chest CT image between COVID-19 and other viral pneumonia with suspected symptoms. Our results do not support CT findings replacing microbiological diagnosis as a critical criterion for COVID-19 diagnosis. Our findings may prompt re-evaluation of isolated patients without laboratory confirmation.

X-Ray Microfocus Radioscopy and Computed Tomography for Failure Analysis

1996 ◽  
Author(s):  
R.H. Bossi ◽  
D.A. Cross ◽  
R.A. Mickelsen
Keyword(s):  
Computed Tomography ◽  
Failure Analysis ◽  
Conventional Radiography ◽  
Ct Images ◽  
Ct Image ◽  
Video Monitor ◽  
Cross Sectional ◽  
X Ray ◽  
Technical Accuracy ◽  
Conventional Film

Abstract X-ray microfocus radioscopy and computed tomography (CT) offer detailed information on the internal assembly and material condition of objects under failure analysis investigation. Using advanced systems for the acquisition of radioscopic and CT images, failure analysis investigations are improved in technical accuracy at a reduced schedule and cost over alternative approaches. A versatile microfocus radioscopic system with CT capability has been successfully implemented as a standard tool in the Boeing Defense & Space Group Failure Analysis Laboratory. Using this tool, studies of electronic, electromechanical and composite material items have been performed. Such a system can pay for itself within two years through higher productivity of the laboratory, increased laboratory value to the company and resolution of critical problems whose worth far exceeds the value of the equipment. The microfocus X-ray source provides projection magnification images that exceed the sensitivity to fine detail that can be obtained with conventional film radiography. Radioscopy, which provides real-time images on a video monitor, allows objects to be readily manipulated and oriented for optimum x-ray evaluation, or monitored during dynamic processes to check performance. Combined with an accurate manipulating stage and data acquisition system x-ray measurements can be used for CT image reconstruction. The CT image provides a cross sectional view of the interior of an object without the interference of superposition of features found in conventional radiography. Accurate dimensional measurements and material constituent identification are possible from the CT images. By taking multiple, contiguous CT slices entire three dimensional data files can be generated of objects.

scholarly journals Chest Computed Tomography Images in Neonatal Bronchial Pneumonia under the Adaptive Statistical Iterative Reconstruction Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Ying Sun ◽  
Liao Wu ◽  
Zhaofang Tian ◽  
Tianping Bao
Keyword(s):  
Computed Tomography ◽  
Iterative Reconstruction ◽  
Peripheral Blood ◽  
Ct Images ◽  
Ct Image ◽  
Adaptive Statistical Iterative Reconstruction ◽  
Chest Computed Tomography ◽  
Ct Examination ◽  
Statistical Iterative Reconstruction ◽  
Subjective Score

This study was to explore the application value of chest computed tomography (CT) images processed by artificial intelligence (AI) algorithms in the diagnosis of neonatal bronchial pneumonia (NBP). The AI adaptive statistical iterative reconstruction (ASiR) algorithm was adopted to reconstruct the chest CT image to compare and analyze the effect of the reconstruction of CT image under the ASiR algorithm under different preweight and postweight values based on the objective measurement and subjective evaluation. 85 neonates with pneumonia treated in hospital from September 1, 2015, to July 1, 2020, were selected as the research objects to analyze their CT imaging characteristics. Subsequently, the peripheral blood of healthy neonates during the same period was collected, and the levels of C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) were detected. The efficiency of CT examination, CRP, ESR, and combined examination in the diagnosis of NBP was analyzed. The results showed that the subjective quality score, lung window subjective score, and mediastinal window subjective score were the highest after CT image reconstruction when the preweight value of the ASiR algorithm was 50%. After treatment, 79 NBP cases (92.9%) showed ground-glass features in CT images. Compared with the healthy neonates, the levels of CRP and ESR in the peripheral blood of neonates with bronchial pneumonia were much lower ( P < 0.05 ). The accuracy rates of CT examination, CRP examination, ESR examination, CRP + ESR examination, and CRP + ESR + CT examination for the diagnosis of NBP were 80.7%, 75.3%, 75.1%, 80.3%, and 98.6%, respectively. CT technology based on AI algorithm showed high clinical application value in the feature analysis of NBP.

Non-Invasive Age Estimation by Cranial Suture Closure in Japanese Sika Deer (Cervus nippon)

Mammal Study ◽  
2019 ◽  
Vol 44 (3) ◽  
pp. 147
Author(s):  
Jinwoo Oh ◽  
Masato Minami ◽  
Suzuna Ikeda ◽  
Seiki Takatsuki ◽  
Nobumasa Oonishi ◽  
...  
Keyword(s):  
Age Estimation ◽  
Sika Deer ◽  
Cervus Nippon ◽  
Cranial Suture ◽  
Non Invasive ◽  
Suture Closure

Computed tomography and radio-graphic assessment of congruity between the ulnar trochlear notch and humeral trochlea in large breed dogs

2017 ◽  
Vol 30 (01) ◽  
pp. 8-14 ◽  
Author(s):  
Mário Ginja ◽  
Armando Fernandes ◽  
António Ferreira ◽  
Pedro Melo-Pinto ◽  
Bruno Colaço ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Intraclass Correlation ◽  
Computer Software ◽  
Ct Images ◽  
Ct Measurements ◽  
Starting Point ◽  
Central Ridge ◽  
Mean Differences ◽  
Extended View ◽  
Lower Limits

Summary Objective: Assess the fit between the ulnar trochlear notch (UTN) and humeral trochlea (HT) in elbow radiographs and computed tomography (CT) images by measuring the curvature radii in normal joints. Methods: Mediolateral extended view (MLE) and CT were performed on 16 elbows from cadaveric dogs weighing over 20 kg. Curves were traced at the subchondral level from the UTN central ridge and the HT sagittal groove related to the UTN on ~132° joint extension. Curvature radii were achieved using appropriate computer software. Results: Intraclass correlation coefficient between MLE/CT measurements were statistically significant, with lower limits of a 95% confidence interval (CI) >0.75. The mean differences between MLE/CT measurements were -0.71 mm (95% CI: -0.97 to -0.45) for UTN and -1.04 mm (95% CI: -1.21 to -0.87) for HT. The UTN and HT curvature radii typology were similar, with maximum radius values at the starting point and two intermediate peaks. The UTN curvature radii were bigger than the HT radii, with the largest differences in the most proximal aspect of the joint and in the second intermediate peak. Clinical significance: To the authors’ knowledge, this is the first report on humeroulnar congruity through curvature radii evaluation. The software and methodology proposed enabled an adequate UTN and HT radii curvature assessment in MLE and CT images. Comparative studies in normal and dysplastic dogs of various breeds could better clarify the role of UTN and HT curvature radii in elbow incongruity and dysplasia.

scholarly journals Intelligent Algorithm-Based Computed Tomography Image Features in Diagnosis of the Effect of Radiofrequency Ablation in Liver Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yufeng Cha ◽  
Zhili Wei ◽  
Chi Ma ◽  
Lei Zhang
Keyword(s):  
Computed Tomography ◽  
Radiofrequency Ablation ◽  
Ct Images ◽  
Segmentation Algorithm ◽  
Control Group ◽  
Observation Group ◽  
Ct Image ◽  
Comprehensive Diagnosis ◽  
Kappa Value ◽  
The Difference

To provide a reference for finding a reasonable evaluation method for treatment effect of radiofrequency ablation (RFA), computed tomography (CT) image optimized by the intelligent segmentation algorithm was utilized to evaluate the liver condition of hepatocellular carcinoma (HCC) patients after RFA and to estimate the patient’s prognosis. Eighty-eight patients with HCC who needed RFA surgery after diagnosis in our hospital were selected. The CT images before optimization were set as the control group; the CT images after optimization were set as the observation group. Comprehensive diagnosis was taken as the gold standard to compare the ablation range and residual lesions under CT scans before and after surgery. The results showed that the consistency of the two sets of CT images was compared with comprehensive diagnosis under different diameters of the lesion. The difference between the two groups was not statistically considerable when the diameter of the lesion was less than 50 mm ( P > 0.05 ). For lesions larger than 50 mm in diameter, the consistency of the observation group (83%) was remarkably higher than that of the control group (40%), and the difference was substantial ( P < 0.05 ). The kappa value of the observation group was 0.84 and that of the control group was 0.78. The kappa value of observation group was better than the control group, with considerable difference ( P < 0.05 ). In conclusion, the diagnostic effect of CT image based on intelligent segmentation algorithm was superior to conventional diagnosis when the diameter of the lesion was larger than 50 mm. Moreover, the overall improvement rate of patients after RFA treatment was far greater than the recurrence rate, indicating that the clinical adoption of RFA was very meaningful.

Cranial suture closure and its implications for age estimation

1994 ◽  
Vol 4 (3) ◽  
pp. 193-207 ◽  
Author(s):  
Catherine A. Key ◽  
Leslie C. Aiello ◽  
Theya Molleson
Keyword(s):  
Age Estimation ◽  
Cranial Suture ◽  
Suture Closure
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