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دسترسی آزاد مقاله
1 - Evaluation of Mandibular Indexes for Sex Estimation by Use of CBCT Imaging in Iranian population samples
Alireza Fereidooni Naghani Arash Ghodousi Roshanak Ghafari Somayeh AbbasiBackground:Identification of skeletal remains is crucial in forensic medicine, and one of the important subjects for identifying skeletal remains is sex estimation. the present study aimed to investigate some of the anthropological features of the mandible used for fore چکیده کاملBackground:Identification of skeletal remains is crucial in forensic medicine, and one of the important subjects for identifying skeletal remains is sex estimation. the present study aimed to investigate some of the anthropological features of the mandible used for forensic sex estimation with the use of CBCT images.Materials & Methods:In this descriptive-analytical study, CBCTs of eighty patients were studied. The studied variables were the mediolateral, and anteroposterior dimensions of the condyle, the ante gonial angle, the longitudinal axis of the condylar angle, and the vertical height of the coronoid process. The above parameters were measured using OnDemand software, and statistical analysis was performed using SPSS software. Independent and Paired T-tests, Discriminant and Receiver operating characteristic (ROC) curves were used for statistical analysis. P values less than 0.05 were considered significant.Results:The condyle mediolateral average dimension for males was significantly higher than for females (p<0.001). Three discriminant analysis models, the first based on the measurements on the right, the second based on the measurements on the left and the third based on mean measurements on both sides, were developed for sex estimation. The area under the receiver operating characteristic (ROC) curve was used for quality assessment of the fitted models and determination of their prediction ability. The ability of all three discriminant models to do sex estimation was obtained by at least 70%. Also, using the ROC curve, the third model was more efficient in sex estimation (area=0.869, p<0.001).Conclusion:The mediolateral dimension of the mandibular condyle process is a useful parameter in sex estimation. Classification accuracy is more than 80% in all models. Different methods should be used together to make more accurate results of sex estimation and one method alone is not sufficiently advised. پرونده مقاله -
دسترسی آزاد مقاله
2 - Prevalence of periapical radiolucency in endodontically treated teeth with untreated canals by CBCT
Sara Barati Azadeh Torkzadeh Parisa Ranjbarian saeed Taraz JamshidiBackground: An untreated root canal in an endodontically treated tooth can cause periapical lesions and as a result necrosis and inflammation of the pulp or destruction of periodontal tissues. The aim of this study was to determine the prevalence of periapical radioluce چکیده کاملBackground: An untreated root canal in an endodontically treated tooth can cause periapical lesions and as a result necrosis and inflammation of the pulp or destruction of periodontal tissues. The aim of this study was to determine the prevalence of periapical radiolucency in endodontically treated teeth with untreated canals by CBCT.Materials & Methods: In this analytical cross-sectional study,a total of 326 maxillary and mandibular premolars and molars with 775 root canals with previous root canal treatment obtained from CBCT images from the archives of the Radiology Center of Azad University of Isfahan (Khorasgan) were examined.The number of teeth and roots, presence/absence of periapical lesions, and presence/absence of untreated canals were recorded. Data were analyzed using chi-square and Fisher's exact testsResults: Untreated canals were observed in 38 cases . The most common type of untreated canal was the second mesiobuccal canal (57.9%) and the maxillary first molar had the highest untreated canal . Apical periodontitis lesions were observed in 125 canals.There was a significant difference between the frequency of untreated canals in the endodontically treated maxillary premolars and molars, mandibular premolars, and molars. There was a significant difference in the frequency of apical periodontitis between endodontically treated maxillary premolars and molars, and mandibular premolars and molars.Conclusion:The frequency of apical periodontitis is most likely higher in the second mesiobuccal canal of maxillary first molars with no successful root canal treatment than in other teeth. پرونده مقاله -
دسترسی آزاد مقاله
3 - Optimal detection of suspected lung nodules using a novel convolution neural network
Reza Majidpourkhoei Mehdi Alilou Kambiz Majidzadeh Amin BabazadehSangarLung cancer is among the deadliest cancers worldwide. One of the indications of lung cancers is lung nodules which can appear individually or attach to the lung wall. Therefore, the detection of the so-called nodules is complicated. In such cases, the image processing a چکیده کاملLung cancer is among the deadliest cancers worldwide. One of the indications of lung cancers is lung nodules which can appear individually or attach to the lung wall. Therefore, the detection of the so-called nodules is complicated. In such cases, the image processing algorithms are performed by the computer, which can aid the radiologists in locating and assessing the nodule's feature. The significant problems with the current systems are the increment of the accuracy, improvement of other criteria in the results, and optimization of the computation costs. The present paper's objective is to efficiently cope with the aforementioned problems by a shallow and light network. Convolutional Neural Networks were utilized to distinguish between benign or malignant lung nodules. In CNN's networks, the complexity increases as the number of layers increases. Accordingly, in the current paper, two scenarios are presented based on State the art and shallow CNN method in order to accurately detect lung nodules in lung CT scans. A subset of the LIDC public dataset including N=7072 CT slices of varying nodule sizes was also used for training and validation of the current approach. Training and validation steps of the network were performed approximately in five hours, and the proposed method achieved a high detection accuracy of 83.6% in Scenario1 and 91.7% in Scenario2. Due to the usage of various validated database images and comparison with previous similar studies in terms of accuracy, the proposed solution achieved a decent trade-off between criteria and saved computation costs. The present work demonstrated that the proposed network was simple and suitable for the so-called problems. Although the paper attempted to meet the existing challenges and fill up the prevailing niches in the literature, there are still further issues that requires complementary studies to shape the tapestry of the knowledge in the field. پرونده مقاله -
دسترسی آزاد مقاله
4 - Enhancing Lung Cancer Diagnosis Accuracy through Autoencoder-Based Reconstruction of Computed Tomography (CT) Lung Images
Mohammad Amin Pirian iman heidari Toktam Khatibi Mohammad Mehdi SepehriLung cancer is a major global cause of cancer-related deaths, emphasizing the importance of early detection through chest imaging. Accurate reconstruction of computed tomography (CT) lung images plays a crucial role in the diagnosis and treatment planning of lung cancer چکیده کاملLung cancer is a major global cause of cancer-related deaths, emphasizing the importance of early detection through chest imaging. Accurate reconstruction of computed tomography (CT) lung images plays a crucial role in the diagnosis and treatment planning of lung cancer patients. However, noise in CT images poses a significant challenge, hindering the precise interpretation of internal tissue structures. Low-dose CT, with reduced radiation risks, has gained popularity. Nonetheless, inherent noise compromises image quality, potentially impacting diagnostic performance. Denoising autoencoder and unsupervised deep learning algorithms offer a promising solution. A dataset of CT images from patients suspected of lung cancer was categorized into four disease groups to evaluate different autoencoder models. Results showed that designed autoencoders effectively reduced noise, enhancing overall image quality. The semi-supervised autoencoder exhibited superior performance, preserving fine details and enhancing diagnostic information. This research underscores autoencoder models' potential in improving lung cancer diagnosis accuracy by reconstructing CT lung images, emphasizing the importance of noise reduction techniques in enhancing image quality and diagnostic performance. پرونده مقاله -
دسترسی آزاد مقاله
5 - Measurement of Effective Dose to Head and Neck Critical Organs in Computed Tomography
Amir Hosein Goodarzi Mastaneh Sanei Hadi Hasanzadeh Zohreh Khosravi Ahmad Bitarafan-Rajabi Alireza EmadiOne of the most effective methods to report organ dose in CT scan (Computed Tomography scan) is to report effective dose. This study aimed to investigate the actual dose during head and neck CT scans using an anthropomorphic head phantom. In this study, an anthropomorph چکیده کاملOne of the most effective methods to report organ dose in CT scan (Computed Tomography scan) is to report effective dose. This study aimed to investigate the actual dose during head and neck CT scans using an anthropomorphic head phantom. In this study, an anthropomorphic phantom was constructed with natural bone and paraffin wax. Then, we considered several sites in the phantom to investigate the dose. These sites include the Brain, Thyroid, Parotid, and Lens, which were filled by Gafchromic films. Finally, we irradiated the phantom using several CT protocols.Our findings indicate that the dose of the considered organs was in the different ranges according to the protocol used. The highest dose range was related to the ten-slice spiral, ranging from 0.75 to 15.8 mGy (Mean). We showed the lowest dose range in SPECT-CT which was in the range of 0.55 to 0.1 mGy (Mean). The absorbed dose of the eyes was much higher in most protocols compared to the other organs. There is also the most significant difference between the lens and the other organs in the ten-slice spiral CT. Comparing the 10 and 256 slice scanners; we showed that the organ dose in the 256 slice is less than ten slices. The lowest mean organ dose (mGy) and SD (Standard Deviation) are related to the SPECT CT, which are 0.76±0.03, 0.95±0.02, 0.78±0.02, and 0.71±0.02 for the brain, parotid, lens, and thyroid, respectively. پرونده مقاله
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