Radiographic Image Quality Research Articles

Charting Ethical Terrain: The Functon of Artificial Intelligence in Oral and Maxillofacial Imaging

The integration of artificial intelligence (AI) into maxillofacial imaging represents a significant advancement in diagnostics and therapy. This review explores the ethical implications of AI in this specialized area, addressing concerns such as data privacy, informed consent, and algorithmic bias. It highlights the potential benefits of AI for patient outcomes and clinical efficiency while acknowledging risks associated with reliance on automated systems. The review aims to establish a framework for ethical guidelines to ensure that AI enhances patient care. AI's application in various industries has gained momentum, with dentistry, particularly oral and maxillofacial radiology, emerging as a promising field. Recent studies have focused on convolutional neural networks for tasks such as image classification, detection, segmentation, and refinement. These AI systems support radiographic diagnosis, image analysis, forensic dentistry, and image quality enhancement. However, optimal performance requires large, well-labeled datasets, necessitating significant input from oral and maxillofacial radiologists, which can be time-intensive. For AI to be effectively integrated into clinical practice, several challenges must be overcome, including the creation of comprehensive open datasets, understanding AI judgment criteria, and addressing DICOM hacking threats. By developing solutions alongside AI advancements, the technology can significantly evolve, potentially transforming automated diagnosis, treatment planning, and tool development. Oral and maxillofacial radiologists will play a crucial role in shaping AI applications in their field, leveraging their expertise in interpreting radiographic images.

Algorithm for Processing X-ray Images Using Fuzzy Logic

Introduction. To improve the diagnostics of knee joint diseases, it is necessary to enhance the quality of processing radiographic images, i.e., to provide experts with more accurate information for pathology analysis. The objective of the study is to demonstrate the capabilities of fuzzy logic in improving the algorithm for determining reference lines and knee flexion angles. This requires a program that analyzes X-ray images. The methods known today, described in scientific and applied literature, are not sufficiently automated. In some cases, orthopedists and surgeons have to manually refine images and adjust lines. This gap is filled by the presented work. The algorithm developed by the author is described. It does not involve human participation and automatically identifies the lines and angles of knee flexion. Based on the result issued by the system, the doctor can, firstly, judge the presence of pathology. Secondly, the information provided by the program allows for more accurate planning, performing operations, and prescribing therapy.Materials and Methods. Images from two X-ray machines operating in Al-Basel Hospital (Latakia, Syria) were used. The Python language was used for the software implementation of the algorithm. The solution was tested on 500 patients at Al-Basel Hospital. The results generated by the new system and previous versions of X-ray image processing programs were compared.Results. An algorithm for constructing reference lines and angles for processing knee joint X-ray images is created, described, and implemented in practice. The capabilities of fuzzy logic in automating double threshold detection when identifying bone boundaries in images are shown. The operation of an improved Gaussian filter designed for processing X-ray images is described. The modified method of knee bone X-ray analysis includes the development of an algorithm for automatic detection of structures and anomalies in knee joints, determination and measurement of anatomical parameters, assessment of the degree of damage, etc. The method for determining the contour boundaries on radiographs combined the Canny detector, the watershed algorithm, and fuzzy logic. The program has been implemented in medical practice and shows 98% accuracy, spending less than 20 seconds to process the image.Discussion and Conclusion. The new system provides high accuracy, acceptable efficiency, and does not require manual correction of images. Experts are now able to identify subtle indicators of disorders. In addition, the new method makes it possible to understand complex cases when several factors are combined, indicating potential pathology. Widespread implementation of the method will improve the quality of medical services in orthopedics. Scientific research in this direction should be continued to expand the set of strategies for the treatment of diseases of the musculoskeletal system. It is necessary to create solutions with absolute accuracy, higher processing efficiency, as well as methods suitable for analyzing other joints.

A new method for evaluating radial neck fractures based on Judet classification.

To propose a new method for evaluating paediatric radial neck fractures and improve the accuracy of fracture angulation measurement, particularly in younger children, and thereby facilitate planning treatment in this population. Clinical data of 117 children with radial neck fractures in our hospital from August 2014 to March 2023 were collected. A total of 50 children (26 males, 24 females, mean age 7.6 years (2 to 13)) met the inclusion criteria and were analyzed. Cases were excluded for the following reasons: Judet grade I and Judet grade IVb (> 85° angulation) classification; poor radiograph image quality; incomplete clinical information; sagittal plane angulation; severe displacement of the ulna fracture; and Monteggia fractures. For each patient, standard elbow anteroposterior (AP) view radiographs and corresponding CT images were acquired. On radiographs, Angle P (complementary to the angle between the long axis of the radial head and the line perpendicular to the physis), Angle S (complementary to the angle between the long axis of the radial head and the midline through the proximal radial shaft), and Angle U (between the long axis of the radial head and the straight line from the distal tip of the capitellum to the coronoid process) were identified as candidates approximating the true coronal plane angulation of radial neck fractures. On the coronal plane of the CT scan, the angulation of radial neck fractures (CTa) was measured and served as the reference standard for measurement. Inter- and intraobserver reliabilities were assessed by Kappa statistics and intraclass correlation coefficient (ICC). Angle U showed the strongest correlation with CTa (p < 0.001). In the analysis of inter- and intraobserver reliability, Kappa values were significantly higher for Angles S and U compared with Angle P. ICC values were excellent among the three groups. Angle U on AP view was the best substitute for CTa when evaluating radial neck fractures in children. Further studies are required to validate this method.

Automatic quality assessment of knee radiographs using knowledge graphs and convolutional neural networks.

X-ray radiography is a widely used imaging technique worldwide, and its image quality directly affects diagnostic accuracy. Therefore, X-ray image quality control (QC) is essential. However, subjectively assessing image quality is inefficient and inconsistent, especially when large amounts of image data are being evaluated. Thus, subjective assessment cannot meet current QC needs. To meet current QC needs and improve the efficiency of image quality assessment, a complete set of quality assessment criteria must be established and implemented using artificial intelligence (AI) technology. Therefore, we proposed a multi-criteria AI system for automatically assessing the image quality of knee radiographs. A knee radiograph QC knowledge graph containing 16 "acquisition technique" labels representing 16 image quality defects and five "clarity" labels representing five grades of clarity were developed. Ten radiographic technologists conducted three rounds of QC based on this graph. The single-person QC results were denoted as QC1 and QC2, and the multi-person QC results were denoted as QC3. Each technologist labeled each image only once. The ResNet model structure was then used to simultaneously perform classification (detection of image quality defects) and regression (output of a clarity score) tasks to construct an image QC system. The QC3 results, comprising 4324 anteroposterior and lateral knee radiographs, were used for model training (70% of the images), validation (10%), and testing (20%). The 865 test set data were used to evaluate the effectiveness of the AI model, and an AI QC result, QC4, was automatically generated by the model after training. Finally, using a double-blind method, the senior QC expert reviewed the final QC results of the test set with reference to the results QC3 and QC4 and used them as a reference standard to evaluate the performance of the model. The precision and mean absolute error (MAE) were used to evaluate the quality of all the labels in relation to the reference standard. For the 16 "acquisition technique" features, QC4 exhibited the highest weighted average precision (98.42%±0.81%), followed by QC3 (91.39%±1.35%), QC2 (87.84%±1.68%), and QC1 (87.35%±1.71%). For the image clarity features, the MAEs between QC1, QC2, QC3, and QC4 and the reference standard were 0.508±0.021, 0.475±0.019, 0.237±0.016, and 0.303±0.018, respectively. The experimental results show that our automated quality assessment system performed well in classifying the acquisition technique used for knee radiographs. The image clarity quality evaluation accuracy of the model must be further improved but is generally close to that of radiographic technologists. Intelligent QC methods using knowledge graphs and convolutional neural networks have the potential for clinical applications.

Artificial intelligence methods in dental radiography

Introduction: The application of artificial intelligence in dentistry can significantly improve the outcome of patient treatment and reduce human error. Computer systems and certain methods that use complex algorithms are able to encode digital data about the radiographic image, obtained by X-ray radiation, and transfer them to a computer language for processing a large set of data. Applied as an auxiliary tool, it can give information about the patient and diagnostics of teeth and surrounding dental structures on radiographic images (two-dimensional and three-dimensional). The aim of the paper: The aim of the paper is to present the development and application of artificial intelligence in dentistry and at the same time emphasizing the importance of segmentation methods and methods of improving the quality of dental radiographic images. Discussion: The common goal of the development and application of artificial intelligence methods in dental radiography is directed on obtaining radiograms from which diagnostically valuable information will be collected faster and easier for the purpose of successful treatment of the patients. Methods of segmentation of a dental structures have been developed to automatically number and localize the tooth or independently mark and display the desired structures on the image. Methods of image quality enhancement tend to work on, for example, improving image resolution or reducing metal artifacts. Research has shown that artificial intelligence can be applied in everyday clinical practice, but it has certain limitations. Conclusion: Artificial intelligence methods in dental radiography are an useful auxiliary tool in clinical dental practice because they can speed up the process of retrieving patient data. Automatic localization of dental structure reduces the dentist's time for manual image analysis, but cannot completely replace human knowledge. For the full implementation of the mentioned methods, more development standards and resources are needed to overcome the ethical and legal problems of replacing humans with computer systems.

CBCT in Dental Implantology: A Key Tool for Preventing Peri-Implantitis and Enhancing Patient Outcomes.

(1) Introduction: Trust is a cornerstone of the patient-physician relationships. Unforeseen complications in the health care system could jeopardize patients' trust in their physicians. (2) Aim: This article presents a quantitative figure regarding foreseeing the necessity of a three-dimensional quantitative visualization of bone structure and concurrently preparing for an ancillary procedure by a dentist to successfully perform the surgery that could minimize unforeseen complications; (3) Materials and method: This retrospective study has been derived based on an analysis of 1134 patients who had received 4800 dental implants from January 2001 to August 2020, out of which 200 cases were randomly selected for this study. Each procedure during implant treatment was categorized as OPG (Orthopantomography) or OPG with CBCT as per all the procedures which included and were coded as follows, 1: Surgery & Restoration, 2: GBR (Guided Bone Regeneration), 3: GTR (Guided Tissue Regeneration), 4: Block Bone Graft, 5: Spreading, 6: Splitting, 7: Internal Sinus, 8: External Sinus, 9: PRF (Platelet Rich Fibrin). Any of the 200 cases in which implant placement could not have been performed for reasons related to a lack of CBCT were selected for this study. The surgery was aborted halfway through without implant placement in these cases due to a lack of bone quantity and/or lack of primary stability. These cases were registered for re-evaluation and statistical analysis; (4) Results: 7% of the cases that used OPG alone led the surgeon to unexpectedly abort in the middle of the surgery without implant placement. All (100%) of the patients who had CBCT during treatment planning were able to receive implants during the surgery. None of the patients left the surgery without receiving implants if CBCT was used (0%); (5) Discussion: Radiographic image quality is defined as the amount of information within the image that allows the radiologist to make a diagnostic decision with a particular level of certainty (Martin et al., 1999) and hence the importance of CBCT. The unexpected 7% of devastating situations for patients who started surgery but did not have implant placement led to [A] aborting the surgery, [B] procedural difficulties requiring an alternative treatment plan, [C] a negative impact on the patient's behavior, and [D] wanting to change doctor due to a lack of trust; (6) Conclusion: This study indicates that in implant dentistry patients' mistrust could be avoided by 7% if CBCT is obtained. It also shows the significance of cone-beam computed tomography as an adjunct to panoramic radiography during the diagnosis and treatment planning phase. The use of panoramic radiography alone can lead to a 7% likelihood of misdiagnosis. A lack of CBCT during treatment planning negatively affects the outcome of surgical procedures.

Partial Adaptive Multi-Level Block Truncation Coding (Ambtc) Of Spinal X-Ray Image For Efficient Compression

This study aims to explore various adaptations of the AMBTC compression model applied to lumbar spine radiographic images, focusing on minimizing image size while preserving essential information. The approach involves adjusting several technical aspects of the AMBTC model, including the number of blocks, block size, and compression rate. The quality of the compressed images is assessed using image quality metrics such as PSNR (Peak Signal-to-Noise Ratio) and MSE (Mean Squared Error). The findings indicate that a modified AMBTC compression model can significantly enhance the quality of lumbar spine radiographic images, evidenced by increased PSNR values, while substantially reducing the file size without compromising crucial image details

CBCT-DRRs superior to CT-DRRs for target-tracking applications for pancreatic SBRT

Objective. In current radiograph-based intra-fraction markerless target-tracking, digitally reconstructed radiographs (DRRs) from planning CTs (CT-DRRs) are often used to train deep learning models that extract information from the intra-fraction radiographs acquired during treatment. Traditional DRR algorithms were designed for patient alignment (i.e. bone matching) and may not replicate the radiographic image quality of intra-fraction radiographs at treatment. Hypothetically, generating DRRs from pre-treatment Cone-Beam CTs (CBCT-DRRs) with DRR algorithms incorporating physical modelling of on-board-imagers (OBIs) could improve the similarity between intra-fraction radiographs and DRRs by eliminating inter-fraction variation and reducing image-quality mismatches between radiographs and DRRs. In this study, we test the two hypotheses that intra-fraction radiographs are more similar to CBCT-DRRs than CT-DRRs, and that intra-fraction radiographs are more similar to DRRs from algorithms incorporating physical models of OBI components than DRRs from algorithms omitting these models. Approach. DRRs were generated from CBCT and CT image sets collected from 20 patients undergoing pancreas stereotactic body radiotherapy. CBCT-DRRs and CT-DRRs were generated replicating the treatment position of patients and the OBI geometry during intra-fraction radiograph acquisition. To investigate whether the modelling of physical OBI components influenced radiograph-DRR similarity, four DRR algorithms were applied for the generation of CBCT-DRRs and CT-DRRs, incorporating and omitting different combinations of OBI component models. The four DRR algorithms were: a traditional DRR algorithm, a DRR algorithm with source-spectrum modelling, a DRR algorithm with source-spectrum and detector modelling, and a DRR algorithm with source-spectrum, detector and patient material modelling. Similarity between radiographs and matched DRRs was quantified using Pearson’s correlation and Czekanowski’s index, calculated on a per-image basis. Distributions of correlations and indexes were compared to test each of the hypotheses. Distribution differences were determined to be statistically significant when Wilcoxon’s signed rank test and the Kolmogorov-Smirnov two sample test returned p ≤ 0.05 for both tests. Main results. Intra-fraction radiographs were more similar to CBCT-DRRs than CT-DRRs for both metrics across all algorithms, with all p ≤ 0.007. Source-spectrum modelling improved radiograph-DRR similarity for both metrics, with all p < 10−6. OBI detector modelling and patient material modelling did not influence radiograph-DRR similarity for either metric. Significance. Generating DRRs from pre-treatment CBCT-DRRs is feasible, and incorporating CBCT-DRRs into markerless target-tracking methods may promote improved target-tracking accuracies. Incorporating source-spectrum modelling into a treatment planning system’s DRR algorithms may reinforce the safe treatment of cancer patients by aiding in patient alignment.

Can Digital Enhancement Restore the Image Quality of Phosphor Plate-Based Radiographs Partially Damaged by Ambient Light?

To assess the effect of digital enhancement on the image quality of radiographs obtained with photostimulable phosphor (PSP) plates partially damaged by ambient light. Radiographs of an aluminum step wedge were obtained using the VistaScan and Express systems. Half of the PSP plates was exposed to ambient light for 0, 10, 30, 60, or 90s before being scanned. The resulting radiographs were exported with and without digital enhancement. Metrics for brightness, contrast, and contrast-to-noise ratio (CNR) were derived, and the ratio of each metric between the exposed-to-light and non-exposed-to-light halves of the radiographs was calculated. The resulting ratios of the radiographs with digital enhancement were subtracted from those without digital enhancement and compared among each other. For the VistaScan system, digital enhancement partially restored brightness, contrast, and CNR. For the Express system, digital enhancement only restored CNR and not the impact of ambient light on brightness and contrast. Specifically, digital enhancement restored 23.48% of brightness for the VistaScan, while percentages below 1% were observed for the Express. Digital enhancement restored 53.25% of image contrast for the VistaScan and 5.79% for the Express; 40.71% of CNR was restored for the VistaScan, and 35% for the Express. Digital enhancement can partially restore the damage caused by ambient light on the brightness and contrast of PSP-based radiographs obtained with the VistaScan, as well as on CNR for the VistaScan and Express systems. The exposure of PSP plates to light can lead to unnecessary retakes and increased patient exposure to X-rays.

Effect of Gonadal Protection on Image Quality in Frontal Hip Radiography

In recent years, there has been a growing movement in Western countries toward the abolition of gonadal protection during radiography. The reasons for this recommendation are that there are few reports of increased risk of genetic effects, that the ovarian dose is not due to direct X-rays but due to internally scattered X-rays that cannot be shielded, and that the presence of gonadal protection may adversely affect the automatic exposure control mechanism and may mask important findings. In addition, the gonadal protection is a large high absorber of X-rays, and its presence in the irradiation field may have some effect on image quality, but the effect of the gonadal protection on image quality has not been clarified. In addition, after the abolition of gonadal protection, the optimal irradiation field setting is expected to become even more important to avoid unnecessary exposure. In this study, we investigated the effect of gonadal protection on image quality in frontal hip radiographs of adults with different radiation qualities and clarified the image quality under conditions in which the irradiation field is appropriately narrowed. Frontal hip radiographs were taken using a human phantom as the subject, and the image quality of the femoral head was evaluated. Two irradiation fields were used: (a) 14×17 inch field and (b) an appropriate field (11.6×15 inch) that does not impair the reference line and image information necessary for reading hip joint images. The imaging tube voltage was set at 70 kV, and conditions for adding a copper filter were also considered. The incident surface air kerma was set to 1.25 mGy. The incident surface dose at this time was sufficiently lower than the diagnostic reference level (2.5 mGy) in Japan and was judged to be appropriate for imaging using an indirect conversion flat panel detector. The image quality evaluation item was the signal difference to noise ratio (SdNR) including scatterers. The SdNR decreased by 4.6% when a gonadal shield was placed, indicating that the gonadal shield reduced image quality. When the irradiation field size was appropriately narrowed down, SdNR slightly increased or decreased depending on the quality of the imaging material, but the change was small compared to the change in SdNR with and without the gonadal protection shield. The results of this study confirm that the elimination of gonadal protection in hip radiography has significant advantages, such as reducing unnecessary X-ray exposure while ensuring image quality, when the irradiation field is set appropriately.

Image Quality Comparison between 10kVp Technique and 15 Percent Rule on AP Supine Abdominal X-ray Examination

The abdomen is one of the thickest parts of the human body and there are challenges in obtaining good images due to the thickness and pathology of the patient during an abdominal X-ray. The 15% rule and the 10 kVp technique are used as exposure manipulation methods in abdominal radiography, however, theoretically, the 15% rule is preferred. The 15% rule provides optimal exposure while the 10 kVp technique is simpler in terms of calculating the exposure factor. These two techniques have their advantages; therefore, this study aims to compare the image quality between the 15% rule and the 10 kVp technique of X-ray supine anteroposterior (AP) abdominal radiography image quality and evaluate whether 10 kVp could be an exposure replacement technique for the 15% rule. Five abdomen radiographic images were taken based on both techniques and evaluated quantitatively using ImageJ software and qualitatively based on scoring by two radiographers. Based on the result of the experimental study, the SNR (signal-to-noise) ratio, CNR (contrast-to-noise ratio) and image mean score had no significant differences (p-value&gt;0.05) between the 10 kVp and 15% rule. In conclusion, the 10 kVp technique is a possible substitution for the 15% rule in obtaining valuable diagnostic image quality during AP abdominal X-ray projection and is more suitable to be implied in clinical settings compared to the 15% rule.

Defect detection enhancement using Gaussian Sparse Models

Detecting defects is critical in industrial fabrication, such as pipe welding, where radiography testing (RT) is the gold standard as a non-destructive method for monitoring weld quality and weld corrosion. The extraction of seamless information from radiographic images is critical for this approach. Image processing techniques can improve the quality of radiographic images by enhancing image contrast, especially in flawed regions. In this study, a method based on Gaussian mixture models was implemented and applied to radiographs of welded objects to improve visualization and detectability. In the Sparse Coding and Gaussian Scale Mixture method (SSC-GSM), the local image patches are described as a mixture of Gaussian distributions. Given the different levels of noise in the individual images, the background was determined and subtracted from each original image. The results show that the proposed techniques can maintain and improve the edge information in radiographs and defective regions. The density of pixels along the analyzed profile lines has yielded enhancement by a factor of approximately two for the reconstructed images as compared to the original images. We tested the SSC-GSM method on GD-Xray database with 68 radiographs of the weld. In total, the SSC-GSM technique can improve the contrast of radiography image by back ground removal method and show the defects better that exist in weld radiographs, compared to traditional method for the detection of weld defects.

Application of Pyramidal Decomposition to Improve Digital Radiography Image Quality

As an effort to create innovation in the world of radiography, it is necessary to develop technology in software. This effort is to improve image quality by using pyramidal decomposition. This digital image decomposition is referred to as pyramid decomposition. The original image is decomposed into several frequency bands, repeatedly divided into high-pass components and low-pass components. The high-pass component is set aside while the low-pass image is subjected to subsequent division. This creates a kind of "3D" stack of image layers. Each layer is at a lower frequency and therefore fuzzier. This processing was pioneered by Philips Healthcare as UNIK (Unified Image Quality Enhancement), and by Agfa as MUSICA (Multi-Scale Image Contrast Amplification) with various innovations. The test image uses digital radiography images resulting from innovation from 14bit RAW digital conversion into JPG format. Image quality is calculated using Mean Square Error (MSE) and Peak Signal Noise Ratio (PSNR). The pyramidal decomposition application succeeded in improving the quality of digital radiography images with an average MSE reduction value of 0.018 and an average PSNR increase of 22.114 dB. Visually, there is a constant increase in contrast and detail, so it can be applied in the medical field.

Face the Future-Artificial Intelligence in Oral and Maxillofacial Surgery.

Artificial intelligence (AI) has emerged as a versatile health-technology tool revolutionizing medical services through the implementation of predictive, preventative, individualized, and participatory approaches. AI encompasses different computational concepts such as machine learning, deep learning techniques, and neural networks. AI also presents a broad platform for improving preoperative planning, intraoperative workflow, and postoperative patient outcomes in the field of oral and maxillofacial surgery (OMFS). The purpose of this review is to present a comprehensive summary of the existing scientific knowledge. The authors thoroughly reviewed English-language PubMed/MEDLINE and Embase papers from their establishment to 1 December 2022. The search terms were (1) "OMFS" OR "oral and maxillofacial" OR "oral and maxillofacial surgery" OR "oral surgery" AND (2) "AI" OR "artificial intelligence". The search format was tailored to each database's syntax. To find pertinent material, each retrieved article and systematic review's reference list was thoroughly examined. According to the literature, AI is already being used in certain areas of OMFS, such as radiographic image quality improvement, diagnosis of cysts and tumors, and localization of cephalometric landmarks. Through additional research, it may be possible to provide practitioners in numerous disciplines with additional assistance to enhance preoperative planning, intraoperative screening, and postoperative monitoring. Overall, AI carries promising potential to advance the field of OMFS and generate novel solution possibilities for persisting clinical challenges. Herein, this review provides a comprehensive summary of AI in OMFS and sheds light on future research efforts. Further, the advanced analysis of complex medical imaging data can support surgeons in preoperative assessments, virtual surgical simulations, and individualized treatment strategies. AI also assists surgeons during intraoperative decision-making by offering immediate feedback and guidance to enhance surgical accuracy and reduce complication rates, for instance by predicting the risk of bleeding.

Role of endodontic treatment related signs for the forensic odontology practice considering real-life quality of comparable radiographs

Background. Real life quality of periapical radiographic images widely varies, while also periapical radiographs not always have been taken at the same angulation, especially in multirooted tooth cases, which in turn potentially may limit the value of obtained information received during endodontic treatment for the further comparative dental identification.&#x0D; Objective. To objectify possibility of using real-life quality periapical radiographs obtained during endodontic treatment for the comparative dental identification.&#x0D; Materials and Methods. Research was organized in the form of cross-sectional hospital-based study. Copies of ten pairs of selected radiographs were distributed for the Set 1 (simulation of ante-mortem images), which contained 10 radiographs of before root canal treatment, and Set 2 (simulation of post-mortem images), which contained 10 radiographs of after endodontic interventions. Set 1 and Set 2 images were randomized, and structured via Google Form, and five teaching assistants from the Department of Restorative Dentistry were asked to match the images through provided Google Form. &#x0D; Results. The range of 50-80% correct pre- and post-treatment images matching levels were registered among five operators. The mean correct matching level reached 68.0 ± 7.2%. Experience within endodontics seems to be valuable regressor regarding outcome performance (p &lt; 0.05), while additional Radiology specialization did not significantly improved performance level for matching pre- and post-treatment images (p &gt; 0.05). Operator graded 5 out of 10 images pair as relatively easy to match, 2 images – as moderately difficult to match, and 3 images – as hard to match (Fig. 3), while their agreement on the obtained above-mentioned scores reached 0.8.&#x0D; Conclusion. Significance of endodontics within forensic odontology field in most cases dictated by using the results of periapical radiology as evidences of ante-mortem origin, while also considering the fact of root canal morphology uniqueness and individualized endodontic treatment pattern consistency both ante- and post-mortem even under the influence of various disturbing factors. On the other hand identification role of endodontic signs may be diminished within the absence of proper quality radiographs, or when such were provided at critically different angulations, while also when endodontic-related evidences could not be supported by dental records.

An AI-based algorithm for the automatic evaluation of image quality in canine thoracic radiographs

The aim of this study was to develop and test an artificial intelligence (AI)-based algorithm for detecting common technical errors in canine thoracic radiography. The algorithm was trained using a database of thoracic radiographs from three veterinary clinics in Italy, which were evaluated for image quality by three experienced veterinary diagnostic imagers. The algorithm was designed to classify the images as correct or having one or more of the following errors: rotation, underexposure, overexposure, incorrect limb positioning, incorrect neck positioning, blurriness, cut-off, or the presence of foreign objects, or medical devices. The algorithm was able to correctly identify errors in thoracic radiographs with an overall accuracy of 81.5% in latero-lateral and 75.7% in sagittal images. The most accurately identified errors were limb mispositioning and underexposure both in latero-lateral and sagittal images. The accuracy of the developed model in the classification of technically correct radiographs was fair in latero-lateral and good in sagittal images. The authors conclude that their AI-based algorithm is a promising tool for improving the accuracy of radiographic interpretation by identifying technical errors in canine thoracic radiographs.

Ambient light exposure of photostimulable phosphor plates: is there a safe limit for acceptable image quality?

To subjectively assess radiographs obtained with photostimulable phosphor (PSP) plates exposed to clinical levels of ambient light prior to read-out to potentially set a safe limit for acceptable image quality. Six dental regions of a dry human skull were X-rayed using PSP plates from VistaScan and Express under four exposure times: 0.1, 0.2, 0.32, and 0.4 s. Before read-out, the PSP plates were exposed to ambient light for 0, 5, 10, 30, 60, and 90 s. Six observers were asked to classify the 288 resulting radiographs as acceptable or unacceptable based on the identification of anatomical structures and global image quality. The number of answers classifying radiographs as unacceptable was used to calculate a rejection rate; a pairwise comparison for better image quality was further conducted among radiographs considered acceptable. Reproducibility was tested by having 25% of all experimental groups reassessed. Intra- and interobserver agreement ranged from 0.87 to 1.00 and from 0.81 to 0.92, respectively. Exposure of PSP plates to ambient light increased rejection rates mostly as of 10 s. In the pairwise comparison, subtle differences were observed between radiographs obtained with PSP plates not exposed and those exposed to ambient light for 5 s. Ambient light exposure of PSP plates impairs the image quality of radiographs. A safe limit of ambient light exposure of 5 s for VistaScan and Express should be considered. Ambient light exposure of PSP plates within safe limits can avoid retakes and reduce unnecessary patient exposure to X-rays.

Development of a radiographic technique for porcine head ballistic research

IntroductionThe porcine model shows structural features comparable to that of humans and are routinely used within research, due to the ethical, legal, and practical use of post-mortem human samples. Methods for obtaining high quality and comparable reference data using standardised acquisition protocols are essential. MethodsThe decapitated heads of three adult white sows were subjected to radiographic imaging before and after cranial trauma (9 mm, Heckler and Koch MP5). Digital radiographs were generated using a Siemens MULTIX TOP system with an Agfa digital detector, with foam blocks and sandbags as ancillary equipment. An iterative approach was adopted by the authors to generate reproducible radiographic views from two perpendicular angles. Specimens were kept at 5 °C and wrapped in polythene bags to reduce the impact of putrefaction. ResultsStandardised head radiography technique was developed for superior-inferior and lateral views demonstrating porcine anatomy. Key parameters included: automatic exposure control for tube current (∼4 mAs), tube voltage of 73 kVp, 100 cm source to image receptor distance, and an anti-scatter grid. Slight variances in specimen morphology, developmental status, and soft tissue changes did not affect imaging outcomes. ConclusionThe technique and positioning proposed in this study allows for the acquisition of high quality and reproducible radiographic images for comparable ballistic research datasets. Specimen positioning and centring of the primary beam may be applied across porcine breeds, although individual radiographic parameters may differ according to equipment specifications and specimen size. Implications for practiceDevelopment of a reproducible radiographic technique of porcine heads in forensic and veterinary research.

DICOM file format has better radiographic image quality than other file formats: an objective study.

This study aimed to assess the influence of the file format on the image quality parameters (image noise, brightness, and uniformity) of periapical radiographs acquired with different digital systems. Radiographic images of an acrylic phantom were acquired with two digital systems - Digora Toto and Express, and exported into five different file formats - TIFF, BMP, DICOM, PNG, and JPEG. Image noise, image brightness (mean of gray values), and image uniformity (standard deviation of gray values) were evaluated in all images. A two-way analysis of variance with Tukey's test as a post-hoc test was used to compare the results, considering the file formats and radiographic systems as the studied factors. A significance level of 5% was adopted for all analyses. The DICOM image file format presented lower image noise, higher brightness (higher mean gray values), and greater image uniformity (p<0.001) than the other file formats, which did not differ from each other for both digital radiography systems (p>0.05). The Express system revealed lower image noise and greater image uniformity than the Digora Toto system regardless of the image file format (p<0.001). Moreover, the Express showed higher brightness than the Digora Toto for all image file formats (p<0.001), except for the DICOM image file format, which did not significantly differ between the digital radiography systems tested (p>0.05). The DICOM image file format showed lower image noise, higher brightness, and greater image uniformity than the other file formats (TIFF, BMP, PNG, and JPEG) in both digital radiography systems tested.

A retrospective evaluation of supine pelvic radiography image quality using centring points and anatomical axial rotation, including reliability of measurements (ARLEX-P STUDY)

IntroductionPelvic radiographs are commonly used for the investigation of a variety of conditions. Comparison between examinations requires a consistent radiographic technique but variations in image quality and radiographic centring points are frequently reported in the literature. The aim of this study was to establish the amount of variation in the radiographic centring point (RCP) and pelvic axial rotation (PAR), with a secondary aim of reporting the reliability of such measures. MethodsUsing a previously acquired imaging archive, 633 adult pelvis/hip radiographs were identified on a Picture Archiving and Communication System (PACS). Radiographs with bilateral prostheses, evidence of acute pelvic trauma, projections acquired on a stretcher/trolley and those demonstrating large discontinuity between the detector and X-ray field centre were excluded. To determine centring point variation (+ values denote superior variations) and axial rotation multiple measurements were obtained from each radiograph. A video was used to train five observers and each of these reviewed ten random cases to determine inter- and intra-rater reliability. One of the five observers then performed the measurements on all remaining radiographs. ResultsFollowing exclusions 380 radiographs were evaluated. The median (IQR) RCP deviation from the inter-acetabular line was +22 (+2 to +43) mm where both iliac crests were present and −29 (−45 to −12) mm where they were not. Eleven (3%) cases demonstrate RCP variation from the midline of greater than 25 mm (no bias towards the left or right side). The median (IQR) PAR was 0.0 (−1.5 to 1.4) degrees with greater variance in PAR for male participants (p = 0.004). Almost 60% of inter-rater ICC measurements were categorised as excellent, good or moderate. ConclusionVariations in RCP and PAR exist when evaluating a sample of routinely acquired pelvis radiographs. Some initial factors, such as sex and sub-examination type (full pelvis [XPEL] or low centred pelvis [XHIPB]) have been identified as having a statistical affect on variability. Further research and methods to standardise radiographic techniques is required and must be multidimensional in nature. Implications for practiceSelection of radiographic technique, including RCP, appears to influence components of the pelvis radiograph. Given the increasing clinical requirements for pelvic radiography further standardisation alongside individual optimisation is warranted.