Background: Different computational methods have been used for the prediction of X-ray spectra and beam quality in diagnostic radiology. The purpose of this study was to compare X-ray beam qualities based on half-value layers (HVLs) determined through measurements and computational model estimations.
Methods: The HVL estimations calculated by IPEM78 (Spectrum Processor of the Institute of Physics and Engineering in Medicine's Report 78) and SpekCalc software were compared with those determined through measurements. In this study, the HVLs of both Philips (Phil) (Philips Healthcare, Best, NL) and General Electric Company (GE) (GE Global Research, Niskayuna, US) diagnostic range X-ray machines (50 kVp to 125 kVp) were evaluated.
Results: In the HVL estimations, SpekCalc and IPEM78 showed maximum differences of 10% and 9%, respectively, compared with direct measurements. Both models provided means and SDs of HVLs that were within 5% of the HVL measurements of GE and Phil machines.
Conclusion: Both computational models provide an alternative method for estimating the HVL of diagnostic range X-ray. These models are user-friendly in predicting HVLs, which are used to characterise the quality of the X-ray beam, and these models provide predictions almost instantly compared with experimental measurements.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3629661 | PMC |
Publication Analysis
Top Keywords
Similar Publications
Radiographic Diagnosis of Anomalous Root Canal Morphology in Patients with Pulpal Diseases at a Tertiary Hospital in Nigeria: A Case Series.
West Afr J Med
September 2024
Department of Restorative Dentistry, University College Hospital, Ibadan, Oyo State, Nigeria. Email: Phone Number: +2348033890679.
Negotiation of the intricate pulp canal space may pose a challenge in endodontic treatment. Consequently, appropriate diagnosis and thorough knowledge of the pattern and distribution of root canal systems are imperative for a more predictable outcome in the treatment of pulp diseases. Accordingly, cone beam computed tomography (CBCT) is deemed appropriate as an adjunctive diagnostic tool in endodontics.
View Article and Find Full Text PDFComparative evaluation of allograft particulate bone and cortical bone blocks combined with xenograft bone for labial bone defects in the aesthetic zone: a prospective cohort study.
BMC Oral Health
January 2025
State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases & Department of Implant Dentistry, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China.
Purpose: This study aimed to evaluate the osteogenic performance of allograft particulate bone and cortical bone blocks combined with xenograft under bovine pericardium membranes, for treating different degrees of labial bone defects in the aesthetic zone.
Materials And Methods: Twenty-four patients with bone defects were divided into two groups based on defect severity (Terheyden 1/4 and 2/4 groups). The Terheyden 1/4 group received granular bone grafts alone, while the Terheyden 2/4 group received cortical bone blocks combined with granular bone grafts.
Assessment of deep learning technique for fully automated mandibular segmentation.
Am J Orthod Dentofacial Orthop
February 2025
Department of Orthodontics, Faculty of Dentistry, Çanakkale Onsekiz Mart University, Çanakkale, Turkey.
Introduction: This study aimed to assess the precision of an open-source, clinician-trained, and user-friendly convolutional neural network-based model for automatically segmenting the mandible.
Methods: A total of 55 cone-beam computed tomography scans that met the inclusion criteria were collected and divided into test and training groups. The MONAI (Medical Open Network for Artificial Intelligence) Label active learning tool extension was used to train the automatic model.
A platform combining automatic segmentation and automatic measurement of the maxillary sinus and adjacent structures.
Clin Oral Investig
January 2025
State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, 610041, China.
Objectives: To develop a platform including a deep convolutional neural network (DCNN) for automatic segmentation of the maxillary sinus (MS) and adjacent structures, and automatic algorithms for measuring 3-dimensional (3D) clinical parameters.
Materials And Methods: 175 CBCTs containing 242 MS were used as the training, validating and testing datasets at the ratio of 7:1:2. The datasets contained healthy MS and MS with mild (2-4 mm), moderate (4-10 mm) and severe (10- mm) mucosal thickening.
Plasma Treatment of Metal Surfaces for Enhanced Bonding Strength of Metal-Polymer Hybrid Structures.
Polymers (Basel)
January 2025
Department of Advanced Materials Engineering for Information and Electronics, Kyung Hee University, Yongin 17104, Republic of Korea.
The adhesion between metals and polymers plays a pivotal role in numerous industrial applications, especially within the automotive and aerospace sectors, where there is a growing demand for materials that are both lightweight and durable. This study introduces an innovative technique to improve the adhesion between a metal and a polymer in hybrid structures through the synergistic use of anodization and plasma treatment. By forming a nanoporous oxide layer on aluminum surfaces, anodization enhances the interface for polymer binding.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!