Imaging Science in Dentistry最新文献

{"title":"Clinical validity and precision of deep learning-based cone-beam computed tomography automatic landmarking algorithm.","authors":"Jungeun Park, Seongwon Yoon, Hannah Kim, Youngjun Kim, Uilyong Lee, Hyungseog Yu","doi":"10.5624/isd.20240009","DOIUrl":"10.5624/isd.20240009","url":null,"abstract":"<p><strong>Purpose: </strong>This study was performed to assess the clinical validity and accuracy of a deep learning-based automatic landmarking algorithm for cone-beam computed tomography (CBCT). Three-dimensional (3D) CBCT head measurements obtained through manual and automatic landmarking were compared.</p><p><strong>Materials and methods: </strong>A total of 80 CBCT scans were divided into 3 groups: non-surgical (39 cases); surgical without hardware, namely surgical plates and mini-screws (9 cases); and surgical with hardware (32 cases). Each CBCT scan was analyzed to obtain 53 measurements, comprising 27 lengths, 21 angles, and 5 ratios, which were determined based on 65 landmarks identified using either a manual or a 3D automatic landmark detection method.</p><p><strong>Results: </strong>In comparing measurement values derived from manual and artificial intelligence landmarking, 6 items displayed significant differences: R U6CP-L U6CP, R L3CP-L L3CP, S-N, Or_R-R U3CP, L1L to Me-GoL, and GoR-Gn/S-N (<i>P</i><0.05). Of the 3 groups, the surgical scans without hardware exhibited the lowest error, reflecting the smallest difference in measurements between human- and artificial intelligence-based landmarking. The time required to identify 65 landmarks was approximately 40-60 minutes per CBCT volume when done manually, compared to 10.9 seconds for the artificial intelligence method (PC specifications: GeForce 2080Ti, 64GB RAM, and an Intel i7 CPU at 3.6 GHz).</p><p><strong>Conclusion: </strong>Measurements obtained with a deep learning-based CBCT automatic landmarking algorithm were similar in accuracy to values derived from manually determined points. By decreasing the time required to calculate these measurements, the efficiency of diagnosis and treatment may be improved.</p>","PeriodicalId":51714,"journal":{"name":"Imaging Science in Dentistry","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11450405/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142382342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Image quality-based dose optimization in pediatric cone-beam computed tomography: A pilot methodological study.","authors":"Hak-Sun Kim, Yoon Joo Choi, Kug Jin Jeon, Sang-Sun Han, Chena Lee","doi":"10.5624/isd.20240030","DOIUrl":"10.5624/isd.20240030","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to propose a methodological approach for reducing the radiation dose in pediatric conebeam computed tomography (CBCT), focusing exclusively on balancing image quality with dose optimization.</p><p><strong>Materials and methods: </strong>The dose-area product (DAP) for exposure was reduced using copper-plate attenuation of an X-ray source. The thickness of copper (Cu) was increased from 0 to 2.2 mm, and 10 different DAP levels were used. The QUART DVT_AP phantom and pediatric radiologic dentiform were scanned under the respective DAP levels. The contrast-to-noise ratio (CNR), image homogeneity, and modulation transfer function (MTF) were analyzed using the QUART DVT_AP phantom. An expert evaluation (overall image grade, appropriateness of field of view, artifacts, noise, and resolution) was conducted using pediatric dentiform images. The critical DAP level was determined based on phantom and dentiform analysis results.</p><p><strong>Results: </strong>CNR and image homogeneity decreased as the DAP was reduced; however, there was an inflection point of image homogeneity at Cu 1.6 mm (DAP=138.00 mGy·cm²), where the value started increasing. The MTF showed constant values as the DAP decreased. The expert evaluation of overall image grades showed \"no diagnostic value\" for dentiform images with Cu 1.9-2.2 mm (DAP=78.00-103.33 mGy·cm²). The images with Cu 0-1.6 mm (DAP=138.00-1697.67 mGy·cm²) had a \"good,\" \"moderate,\" or \"poor but interpretable\" grade.</p><p><strong>Conclusion: </strong>Reducing DAP beyond a 1.6-mm Cu thickness degraded CBCT image quality. Image homogeneity and clinical image grades indicated crucial decision points for DAP reduction in pediatric CBCT scans.</p>","PeriodicalId":51714,"journal":{"name":"Imaging Science in Dentistry","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11450406/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142382361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Opportunistic investigation of vascular calcification using 3-dimensional dental imaging.","authors":"Masoud MiriMoghaddam, Hollis Lai, Camila Pacheco-Pereira","doi":"10.5624/isd.20240039","DOIUrl":"10.5624/isd.20240039","url":null,"abstract":"<p><strong>Purpose: </strong>Given the growing use of cone-beam computed tomography (CBCT) scans, this study assessed radiation exposure from these scans in the context of national guidelines and recommended dose limits.</p><p><strong>Materials and methods: </strong>The current literature was reviewed to quantify the benefit of opportunistic diagnosis of carotid artery calcification relative to the potential risk of radiation-induced cancer.</p><p><strong>Results: </strong>The average radiation from CBCT at its largest field of view and highest resolution possible amounts to a reasonable but still low ionizing radiation exposure. This exposure is comparable to 22 days of background radiation and is notably lower than the radiation exposure from medical CT scans. According to the risk assessment analysis, the risk of stroke events involving internal and external carotid artery calcification (CAC) was 202 and 67 per 100,000 individuals, respectively. In contrast, the estimated risk of radiation-induced cancer associated with CBCT was notably lower, at 0.6 per 100,000.</p><p><strong>Conclusion: </strong>The present study advocates for a comprehensive assessment of CBCT scans encompassing the areas of the internal and external carotid arteries by a knowledgeable professional, given the potential advantages of early detection of vascular abnormalities. Dental professionals who take scans involving these areas need to be mindful of reporting these findings and refer patients to their primary care physician for further investigation.</p>","PeriodicalId":51714,"journal":{"name":"Imaging Science in Dentistry","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11450408/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142382363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Finite element analysis of stabilization splint pressure distribution in a patient with disc displacement without reduction: A preliminary study.","authors":"Acing Habibie Mude, Muhammad Ikbal, Mukhsan Putra Hatta, Irfan Sugianto, Edy Machmud, Fadhlil Ulum A Rahman, Imran Irsal, Eka Fibrianti, Muthia Mutmainnah Bachtiar, Thalib Rifky Abdullah Syeban Attamimi","doi":"10.5624/isd.20240017","DOIUrl":"10.5624/isd.20240017","url":null,"abstract":"<p><strong>Purpose: </strong>This study was performed to investigate the pattern of condylar pressure distribution in the discs of a patient diagnosed with disc displacement without reduction.</p><p><strong>Materials and methods: </strong>This research consisted of a pre- and post-test observational clinical study. A patient diagnosed with disc displacement without reduction underwent treatment with an occlusal splint for 3 months. Finite element analysis employed a 3-dimensional model constructed from magnetic resonance images of the patient, taken both before the application of the splint and 3 months after its use.</p><p><strong>Results: </strong>The post-test model demonstrated a decrease in condylar pressure on the disc, with measurements dropping to 72 MPa from the pre-test level of 143 MPa. In the pre-test, the pressure distribution pattern was concentrated on the lateral posterior border, whereas in the post-test, it shifted toward the intermediate zone of the disc.</p><p><strong>Conclusion: </strong>Utilization of a stabilization splint for 3 months resulted in decreased pressure and a marked change in the pressure distribution pattern on the temporomandibular disc.</p>","PeriodicalId":51714,"journal":{"name":"Imaging Science in Dentistry","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11450416/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142382346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-resolution magnetic resonance imaging of teeth and periodontal tissues using a microscopy coil.","authors":"Shinya Kotaki, Hiroshi Watanabe, Junichiro Sakamoto, Ami Kuribayashi, Marino Araragi, Hironori Akiyama, Yoshiko Ariji","doi":"10.5624/isd.20240052","DOIUrl":"10.5624/isd.20240052","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to assess the performance of 2-dimensional (2D) imaging with microscopy coils in delineating teeth and periodontal tissues compared with conventional 3-dimensional (3D) imaging on a 3 T magnetic resonance imaging (MRI) unit.</p><p><strong>Materials and methods: </strong>Twelve healthy participants (4 men and 8 women; mean age: 25.6 years; range: 20-52 years) with no dental symptoms were included. The left mandibular first molars and surrounding periodontal tissues were examined using the following 2 sequences: 2D proton density-weighted (PDw) images and 3D enhanced T1 high-resolution isotropic volume excitation (eTHRIVE) images. Two-dimensional MRI images were taken using a 3 T MRI unit and a 47 mm microscopy coil, while 3D MRI imaging used a 3 T MRI unit and head-neck coil. Oral radiologists assessed dental and periodontal structures using a 4-point Likert scale. Inter- and intra-observer agreement was determined using the weighted kappa coefficient. The Wilcoxon signed-rank test was used to compare 2D-PDw and 3D-eTHRIVE images.</p><p><strong>Results: </strong>Qualitative analysis showed significantly better visualization scores for 2D-PDw imaging than for 3D-eTHRIVE imaging (Wilcoxon signed-rank test). 2D-PDw images provided improved visibility of the tooth, root dental pulp, periodontal ligament, lamina dura, coronal dental pulp, gingiva, and nutrient tract. Inter-observer reliability ranged from moderate agreement to almost perfect agreement, and intra-observer agreement was in a similar range.</p><p><strong>Conclusion: </strong>Two-dimensional-PDw images acquired using a 3 T MRI unit and microscopy coil effectively visualized nearly all aspects of teeth and periodontal tissues.</p>","PeriodicalId":51714,"journal":{"name":"Imaging Science in Dentistry","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11450415/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142382360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Imaging aspects of maxillomandibular bone alterations in patients with multiple myeloma treated with bisphosphonates: A systematic review.","authors":"Amanda Katarinny Goes Gonzaga, Hannah Gil de Farias Morais, Camila Dayla Melo Oliveira, Magda Lyce Rodrigues Campos, Carolina Raiane Leite Dourado Maranhão Diaz, Marcos Custódio, Natália Silva Andrade, Thalita Santana","doi":"10.5624/isd.20240032","DOIUrl":"10.5624/isd.20240032","url":null,"abstract":"<p><strong>Purpose: </strong>Multiple myeloma (MM) is a rare cancer that is typically managed with bisphosphonates to slow bone resorption and prevent skeletal complications. This study aimed to identify imaging patterns in MM patients receiving bisphosphonate therapy.</p><p><strong>Materials and methods: </strong>This systematic review included studies investigating maxillomandibular bone alterations based on imaging examinations in MM patients treated with bisphosphonates. The selected studies were qualitatively assessed using the Critical Appraisal Tools from SUMARI.</p><p><strong>Results: </strong>Six studies, involving 669 MM patients, were included, with 447 receiving bisphosphonate treatment. The majority were treated with pamidronate, zoledronate, or a combination of both. Seventy patients developed medication-related osteonecrosis of the jaw (MRONJ), predominantly in the mandible, characterized by the presence of bony sequestrum, bone sclerosis, increased periodontal ligament space, osteolytic lesions, and osteomyelitis as observed in imaging analyses. For non-MRONJ lesions, the mandible also exhibited the highest frequency of asymptomatic bone alterations. These ranged from \"punched-out\" osteolytic lesions or \"soap bubble\" lesions to solitary bone lesions, areas of bone sclerosis, abnormalities of the hard palate, osteoporosis, non-healed alveoli, and cortical bone rupture.</p><p><strong>Conclusion: </strong>MM patients treated with bisphosphonates display radiographic patterns of maxillomandibular bone lesions. These patterns aid in diagnosis and facilitate early and targeted treatment, thereby contributing to improved morbidity outcomes for these patients.</p>","PeriodicalId":51714,"journal":{"name":"Imaging Science in Dentistry","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11450414/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142382362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Classification of mandibular molar furcation involvement in periapical radiographs by deep learning.","authors":"Katerina Vilkomir, Cody Phen, Fiondra Baldwin, Jared Cole, Nic Herndon, Wenjian Zhang","doi":"10.5624/isd.20240020","DOIUrl":"10.5624/isd.20240020","url":null,"abstract":"<p><strong>Purpose: </strong>The purpose of this study was to classify mandibular molar furcation involvement (FI) in periapical radiographs using a deep learning algorithm.</p><p><strong>Materials and methods: </strong>Full mouth series taken at East Carolina University School of Dental Medicine from 2011-2023 were screened. Diagnostic-quality mandibular premolar and molar periapical radiographs with healthy or FI mandibular molars were included. The radiographs were cropped into individual molar images, annotated as \" healthy\" or \" FI,\" and divided into training, validation, and testing datasets. The images were preprocessed by PyTorch transformations. ResNet-18, a convolutional neural network model, was refined using the PyTorch deep learning framework for the specific imaging classification task. CrossEntropyLoss and the AdamW optimizer were employed for loss function training and optimizing the learning rate, respectively. The images were loaded by PyTorch DataLoader for efficiency. The performance of ResNet-18 algorithm was evaluated with multiple metrics, including training and validation losses, confusion matrix, accuracy, sensitivity, specificity, the receiver operating characteristic (ROC) curve, and the area under the ROC curve.</p><p><strong>Results: </strong>After adequate training, ResNet-18 classified healthy <i>vs</i>. FI molars in the testing set with an accuracy of 96.47%, indicating its suitability for image classification.</p><p><strong>Conclusion: </strong>The deep learning algorithm developed in this study was shown to be promising for classifying mandibular molar FI. It could serve as a valuable supplemental tool for detecting and managing periodontal diseases.</p>","PeriodicalId":51714,"journal":{"name":"Imaging Science in Dentistry","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11450411/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142382341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Erratum to: McCune-Albright syndrome with acromegaly: A case report with characteristic radiographic features of fibrous dysplasia.","authors":"Han-Gyeol Yeom, Byung-Do Lee","doi":"10.5624/isd.20240820","DOIUrl":"https://doi.org/10.5624/isd.20240820","url":null,"abstract":"<p><p>[This corrects the article on p. 421 in vol. 52, PMID: 36605861.].</p>","PeriodicalId":51714,"journal":{"name":"Imaging Science in Dentistry","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11450413/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142382344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combination of metal artifact reduction and sharpening filter application for horizontal root fracture diagnosis in teeth adjacent to a zirconia implant.","authors":"Débora Costa Ruiz, Larissa de Oliveira Reis, Rocharles Cavalcante Fontenele, Murilo Miranda-Viana, Amanda Farias-Gomes, Deborah Queiroz Freitas","doi":"10.5624/isd.20240056","DOIUrl":"10.5624/isd.20240056","url":null,"abstract":"<p><strong>Purpose: </strong>This study examined the influence of metal artifact reduction (MAR), the application of sharpening filters, and their combination on the diagnosis of horizontal root fracture (HRF) in teeth adjacent to a zirconia implant on cone-beam computed tomography (CBCT) examinations.</p><p><strong>Materials and methods: </strong>Nineteen single-rooted teeth (9 with HRF and 10 without) were individually positioned in the right central incisor socket of a dry human maxilla. A zirconia implant was placed adjacent to each tooth. Imaging was performed using an OP300 Maxio CBCT (Instrumentarium, Tuusula, Finland) unit with the following settings: a current of 8 mA, both MAR modes (enabled and disabled), a 5×5 cm field of view, a voxel size of 0.085 mm, and a peak kilovoltage of 90 kVp. Four oral and maxillofacial radiologists independently evaluated the CBCT scans under both MAR conditions and across 3 levels of sharpening filter application (none, Sharpen 1×, and Sharpen 2×). Diagnostic metrics were calculated and compared using 2-way analysis of variance (α=5%). The weighted kappa test was used to assess intra- and inter-examiner reliability in the diagnosis of HRF.</p><p><strong>Results: </strong>MAR tool activation, sharpening filter use, and their combination did not significantly impact the area under the receiver operating characteristic curve, sensitivity, or specificity of HRF diagnosis (<i>P</i>>0.05). Intra- and inter-examiner agreement ranged from fair to substantial.</p><p><strong>Conclusion: </strong>The diagnosis of HRF in a tooth adjacent to a zirconia implant is not affected by the activation of MAR, the application of a sharpening filter, or the combination of these tools.</p>","PeriodicalId":51714,"journal":{"name":"Imaging Science in Dentistry","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11450410/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142382343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of deep learning and convolutional neural network algorithms for mandibular fracture detection using radiographic images: A systematic review and meta-analysis.","authors":"Mahmood Dashti, Sahar Ghaedsharaf, Shohreh Ghasemi, Niusha Zare, Elena-Florentina Constantin, Amir Fahimipour, Neda Tajbakhsh, Niloofar Ghadimi","doi":"10.5624/isd.20240038","DOIUrl":"10.5624/isd.20240038","url":null,"abstract":"<p><strong>Purpose: </strong>The use of artificial intelligence (AI) and deep learning algorithms in dentistry, especially for processing radiographic images, has markedly increased. However, detailed information remains limited regarding the accuracy of these algorithms in detecting mandibular fractures.</p><p><strong>Materials and methods: </strong>This meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Specific keywords were generated regarding the accuracy of AI algorithms in detecting mandibular fractures on radiographic images. Then, the PubMed/Medline, Scopus, Embase, and Web of Science databases were searched. The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool was employed to evaluate potential bias in the selected studies. A pooled analysis of the relevant parameters was conducted using STATA version 17 (StataCorp, College Station, TX, USA), utilizing the metandi command.</p><p><strong>Results: </strong>Of the 49 studies reviewed, 5 met the inclusion criteria. All of the selected studies utilized convolutional neural network algorithms, albeit with varying backbone structures, and all evaluated panoramic radiography images. The pooled analysis yielded a sensitivity of 0.971 (95% confidence interval [CI]: 0.881-0.949), a specificity of 0.813 (95% CI: 0.797-0.824), and a diagnostic odds ratio of 7.109 (95% CI: 5.27-8.913).</p><p><strong>Conclusion: </strong>This review suggests that deep learning algorithms show potential for detecting mandibular fractures on panoramic radiography images. However, their effectiveness is currently limited by the small size and narrow scope of available datasets. Further research with larger and more diverse datasets is crucial to verify the accuracy of these tools in in practical dental settings.</p>","PeriodicalId":51714,"journal":{"name":"Imaging Science in Dentistry","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11450407/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142382345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}