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This study assesses radiation doses in multi-slice computed tomography (CT) using epoxy resin and PMMA phantoms, focusing on the relationship between TAR (tissue air ratio) and kilovoltage peak (kVp). The research was conducted using a Hitachi Supria 16-slice CT scanner. An epoxy resin phantom was fabricated from commercially available materials, to simulate human tissue.

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Unlabelled: This study investigates the anatomical prerequisites that could contribute to the development of this condition.

Material And Methods: Using multi-slice computed tomography (MSCT), the study examined the structure and relationships of key anatomical features, including the alveolar process, sinus wall thickness, and the position of the teeth in relation to the maxillary sinus.

Results: The results revealed that the lower wall of the maxillary sinus is predominantly formed by the alveolar process, with significant variability in wall thickness, especially between the central and lateral regions.

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Article Synopsis
  • This study investigates the effectiveness of single-slice versus multi-slice computed tomography (CT) methods in analyzing body composition in patients with oesophagogastric cancer, focusing on their correlation and impact on survival rates.
  • Researchers examined CT scans of 504 patients, comparing measurements of skeletal muscle, subcutaneous, visceral, and intermuscular adipose tissue, finding high correlation and narrow limits of agreement between the two methods.
  • Results indicate that both measurement techniques offer similar insights into body composition, suggesting that the clinical use of multi-slice analyses may be beneficial but requires further exploration for optimal application.
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Objectives: To develop a deep-learning model for supervised classification of myocardial iron overload (MIO) from magnitude T2* multi-echo MR images.

Materials And Methods: Eight hundred twenty-three cardiac magnitude T2* multi-slice, multi-echo MR images from 496 thalassemia major patients (285 females, 57%), labeled for MIO level (normal: T2* > 20 ms, moderate: 10 ≤ T2* ≤ 20 ms, severe: T2* < 10 ms), were retrospectively studied. Two 2D convolutional neural networks (CNN) developed for multi-slice (MS-HippoNet) and single-slice (SS-HippoNet) analysis were trained using 5-fold cross-validation.

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Background: Coronary calcification is a well-established risk factor for cardiovascular events. This retrospective study sought to determine the predictive value of coronary calcification in a specific group of patients with chronic kidney disease.

Methods: We included 1094 asymptomatic patients (724 males, 370 females, age 62 ± 9.

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