List of Articles CT Scan

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  1 - Investigating the improvement of the quality of CT scan images in the presence of metal implants in the body
  Jalal AminRezaei Fataneh Taghizadeh-Farahmand
  Objective: CT scan imaging is one of the imaging methods for better diagnosis of some diseases. But in this imaging method, there is a possibility of correct diagnosis of diseases due to the presence of metal plates. The presence of such false images mostly occurs in th More

  Objective: CT scan imaging is one of the imaging methods for better diagnosis of some diseases. But in this imaging method, there is a possibility of correct diagnosis of diseases due to the presence of metal plates. The presence of such false images mostly occurs in the images of the pelvis and head, which causes the lack of correct and early diagnosis of diseases such as colon cancer, cerebral hemorrhage, and stroke. In this regard, the aim of the present study is to investigate the improvement of the quality of CT scan images in the presence of metal implants in the body.Materials and methods: In this research, the basis of the proposed method is based on interpolation and segmentation, which is achieved through nine stages of image processing with high quality compared to previous methods. The steps are as follows: improving image quality, removing regions of metal parts, segmenting metal parts, transferring the image to the sinogram area, linear interpolation of paths, normalizing the sinogram, interpolating paths, filtering, adding metal parts.Findings: The present study showed that the effectiveness of the proposed method on large and small implants has a higher quality than the two methods of interpolation of general changes and linear interpolation, and it has a more suitable quality than the method of removing metal parts for large implants.Conclusion: The proposed method has a more acceptable and more efficient performance in the pelvic region than the two linear and elimination interpolation methods compared. Manuscript profile
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  2 - Synthesis and application of the Iron Oxide nanoparticles with Iodine containing coating in dual CT-MR imaging
  R. Ahmadi M.H. Shaeri
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  3 - Bone Surface Model Development Based on Point Clouds Extracted From CT Scan Images
  I. Asheghi Bonabi S. J. Hemmati
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  4 - An Intelligent Method for Death Prediction Using Patient Age and Bleeding Volume on CT scan
  Yosra Azizi Nasrabadi Ali Jamali Nazari Hamid Ghadiri Farshid Babapour Mofrad
  The purpose of this paper's prediction of survival or death within 30 days is based on a cerebral hemorrhage. Timely and correct diagnosis and treatment of cerebral hemorrhage are essential. If the patient's death is predicted during these thirty days, the treating phys More

  The purpose of this paper's prediction of survival or death within 30 days is based on a cerebral hemorrhage. Timely and correct diagnosis and treatment of cerebral hemorrhage are essential. If the patient's death is predicted during these thirty days, the treating physician should use intensive care and more treatment for the patient. Cerebral hemorrhages require immediate treatment and rapid and accurate diagnosis. In this article, using the volume of cerebral hemorrhage and the patient's age and using the neural network of support vector machine (SVM), it is predicted what percentage of people with cerebral hemorrhage survive and what percentage die. Parameters of cerebral hemorrhage volume and, age of patients, neural network input are considered. The network's output is the survival or death of patients with cerebral hemorrhage over the next thirty days. The data we used included the bleeding volume and age of 66 patients with lobar hemorrhage, 76 patients with deep bleeding, nine patients with Pontine hemorrhage and 11 patients with cerebellar hemorrhage. All bleeding models are considered as input to the support vector machine neural network. The overall accuracy of the designed support vector machine neural network is 93%. Regardless of the type of cerebral hemorrhage, the survival or death of people with cerebral hemorrhage within 30 days is predicted. Manuscript profile
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  5 - An Automatic Model Combining Descriptors of Gray-Level Co-Occurrence Matrix and HMAX Model for Adaptive Detection of Liver Disease in CT Images
  Sanaz Bagheri Somayeh Saraf Esmaili
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  6 - In vitro investigation of the GdF3:Bi nanoparticles synthesized via hydrothermal method as the dual MRI-CT contrast agent
  Mohammad Abbasi رضا احمدی Amirhossein Moghanian Aazam Jannati Esfehani
  In the present study, the Bismuth doped GdF3 nanoparticles were synthesized via the hydrothermal method and the effect of temperature, time and NH4F concentration was investigated. The Poly Ethylene Glycol was used as the surfactant. The phases characterization was indu More

  In the present study, the Bismuth doped GdF3 nanoparticles were synthesized via the hydrothermal method and the effect of temperature, time and NH4F concentration was investigated. The Poly Ethylene Glycol was used as the surfactant. The phases characterization was inducted via XRD, FE-SEM and EDS techniques. The in vitro investigation of the samples as the contast agents were performed using MR and CT imaging. the sample synthesized at 180 oC,, 6 hours and the NH4F concentration twice the Stoichiometric concentration that had the semi spherical structure with mean size lower than 100 nm was the suitable sample and the in vitro studies show that the particles act as an excellent CT contrast agent and also as an effective MRI contrast agent at concentrations between 22.5 and 180 mM. Briefly, The use of Bismuth dopant ant GdF3 nanoparticles was successfully performed and The particles can used as the potential MRI-CT contrast agents. Manuscript profile
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  7 - An Ensemble Deep Learning Model for Detection Covid-19 from CT Scan Images
  حبیب ایزدخواه
  Diagnosis of covid-19 using deep learning on CT scan images can play an important role in helping doctors. In this paper, by combining EfficientNet-B2 and vision transformers (V iT − 1 − 32) neural networks a new deep transfer learning is proposed. For evaluation, con-f More

  Diagnosis of covid-19 using deep learning on CT scan images can play an important role in helping doctors. In this paper, by combining EfficientNet-B2 and vision transformers (V iT − 1 − 32) neural networks a new deep transfer learning is proposed. For evaluation, con-fusion matrix, precision, accuracy, recall, and F1 score are used. The experimental results are 0.9838 for validation accuracy, 0.9667 for test accuracy, and 0.9839 for accuracy. Manuscript profile