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    Automatic maxillary sinus segmentation and pathology classification on cone-beam computed tomographic images using deep learning
    (Bmc, 2024) Altun, Oguzhan; Ozen, Duygu Celik; Duman, Suayip Burak; Dedeoglu, Numan; Bayrakdar, Ibrahim Sevki; Eser, Gozde; Celik, Ozer
    BackgroundMaxillofacial complex automated segmentation could alternative traditional segmentation methods to increase the effectiveness of virtual workloads. The use of DL systems in the detection of maxillary sinus and pathologies will both facilitate the work of physicians and be a support mechanism before the planned surgeries.ObjectiveThe aim was to use a modified You Only Look Oncev5x (YOLOv5x) architecture with transfer learning capabilities to segment both maxillary sinuses and maxillary sinus diseases on Cone-Beam Computed Tomographic (CBCT) images.MethodsData set consists of 307 anonymised CBCT images of patients (173 women and 134 males) obtained from the radiology archive of the Department of Oral and Maxillofacial Radiology. Bilateral maxillary sinuses CBCT scans were used to identify mucous retention cysts (MRC), mucosal thickenings (MT), total and partial opacifications, and healthy maxillary sinuses without any radiological features.ResultsRecall, precision and F1 score values for total maxillary sinus segmentation were 1, 0.985 and 0.992, respectively; 1, 0.931 and 0.964 for healthy maxillary sinus segmentation; 0.858, 0.923 and 0.889 for MT segmentation; 0.977, 0.877 and 0.924 for MRC segmentation; 1, 0.942 and 0.970 for sinusitis segmentation.ConclusionThis study demonstrates that maxillary sinuses can be segmented, and maxillary sinus diseases can be accurately detected using the AI model.
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    Classification of temporomandibular joint osteoarthritis on cone beam computed tomography images using artificial intelligence system
    (Wiley, 2023) Eser, Gozde; Duman, Suayip Burak; Bayrakdar, Ibrahim Sevki; Celik, Ozer
    BackgroundThe use of artificial intelligence has many advantages, especially in the field of oral and maxillofacial radiology. Early diagnosis of temporomandibular joint osteoarthritis by artificial intelligence may improve prognosis. ObjectiveThe aim of this study is to perform the classification of temporomandibular joint (TMJ) osteoarthritis and TMJ segmentation on cone beam computed tomography (CBCT) sagittal images with artificial intelligence. ResultsThe sensitivity, precision and F1 scores of the model for TMJ osteoarthritis classification are 1, 0.7678 and 0.8686, respectively. The accuracy value for classification is 0.7678. The prediction values of the classification model are 88% for healthy joints, 70% for flattened joints, 95% for joints with erosion and 86% for joints with osteophytes. The sensitivity, precision and F1 score of the YOLOv5 model for TMJ segmentation are 1, 0.9953 and 0.9976, respectively. The AUC value of the model for TMJ segmentation is 0.9723. In addition, the accuracy value of the model for TMJ segmentation was found to be 0.9953. ConclusionArtificial intelligence model applied in this study can be a support method that will save time and convenience for physicians in the diagnosis of the disease with successful results in TMJ segmentation and osteoarthritis classification.
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    Comparison of stimulated and unstimulated salivary gland parenchyma using fractal analysis of ultrasonographic images
    (Springer, 2025) Dedeoglu, Numan; Altun, Oguzhan; Ozen, Duygu Celik; Eser, Gozde
    Objective To compare the fractal analysis data of ultrasonography (USG) images of the submandibular and parotid glands before and after parenchymal stimulation to assess for any changes. Methods The study was conducted by taking 240 USG images of bilateral parotid and submandibular glands of 30 patients before and after stimulation. Patients chewed gum for stimulating their salivary glands. Fractal analysis was performed on the USG images, and the data obtained were statistically compared. Results The fractal analysis value of the USG images of the parotid gland was 1.45, both before and after stimulation, indicating no statistically significant difference (p = 0.866). In the submandibular gland, this value was the same before and after stimulation (fractal analysis = 1.42), showing no statistically significant difference (p = 0.748). Parotid and submandibular glands were compared. USG fractal analysis values before and after stimulation and the overall values were statistically significantly different between the different salivary glands (p < 0.05). Conclusion According to fractal analysis, there was no change in the parenchyma of the submandibular and parotid glands despite the stimulation. Submandibular and parotid glands could be distinguished by fractal analysis.
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    Detecting the presence of taurodont teeth on panoramic radiographs using a deep learning-based convolutional neural network algorithm
    (Springer, 2023) Duman, Sacide; Yilmaz, Emir Faruk; Eser, Gozde; Celik, Ozer; Bayrakdar, Ibrahim Sevki; Bilgir, Elif; Ferreira Costa, Andre Luiz
    Objectives Artificial intelligence (AI) techniques like convolutional neural network (CNN) are a promising breakthrough that can help clinicians analyze medical imaging, diagnose taurodontism, and make therapeutic decisions. The purpose of the study is to develop and evaluate the function of CNN-based AI model to diagnose teeth with taurodontism in panoramic radiography. Methods 434 anonymized, mixed-sized panoramic radiography images over the age of 13 years were used to develop automatic taurodont tooth segmentation models using a Pytorch implemented U-Net model. Datasets were split into train, validation, and test groups of both normal and masked images. The data augmentation method was applied to images of trainings and validation groups with vertical flip images, horizontal flip images, and both flip images. The Confusion Matrix was used to determine the model performance. Results Among the 43 test group images with 126 labels, there were 109 true positives, 29 false positives, and 17 false negatives. The sensitivity, precision, and F1-score values of taurodont tooth segmentation were 0.8650, 0.7898, and 0.8257, respectively. Conclusions CNN's ability to identify taurodontism produced almost identical results to the labeled training data, and the CNN system achieved close to the expert level results in its ability to detect the taurodontism of teeth.
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    Five-year change of panoramic radiomorphometric indices and fractal dimension values in type 2 diabetes patients
    (Springer, 2024) Dedeoglu, Numan; Eser, Gozde; Ozen, Duygu Celik; Altun, Oguzhan
    ObjectivesDiabetes mellitus is a chronic disease characterized by dysregulation of glucose metabolism, with characteristic long-term complications accompanied by changes in bone quality. The purpose of this study is to compare the results with a control group by performing radiomorphometric analyses on panoramic radiographs obtained 5 years apart to examine changes in the mandibular bone cortex and microstructures of type 2 diabetes mellitus (T2DM) patients.MethodsTwo panoramic radiographs that were taken 5 years (mean 5.26 +/- 0.134) apart from 52 patients with T2DM (n:26) and a control group (n:26) were used. A total of 104 images were evaluated. Analyses were done from the condyle (FD1), angulus (FD2), distal second premolar apex (FD3), and anterior to the mental foramen (FD4) for fractal dimension (FD) in the mandible. Symphysis index (SI), anterior index (AI), molar index (MI), posterior index (PI), and panoramic mandibular index (PMI) measurements were taken for cortical analysis. Three-way ANOVA, three-way robust ANOVA, two-way ANOVA, and two-way robust ANOVA tests were used for statistical analysis (p < 0.05).ResultsAfter a 5-year period, there was a significant decrease in all FD measures of the mandible in both T2DM and control groups (p < 0.05). This resulted in a statistical difference in the main effect of time. After a 5-year period, no significant difference in mandibular cortical measures was identified between the T2DM and control groups (p > 0.05).ConclusionAccording to panoramic radiography, the mandibular trabecular structure deteriorated after 5 years, whereas cortical values remained the same. It concluded that T2DM had no effect on these results.
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    In-vitro Diagnosis of Approximal Caries in Teeth Periapical Radiography with Different Exposure Parameters
    (Pera Yayincilik Hizmetleri, 2023) Altun, Oguzhan; Ozen, Duygu Celik; Dedeoglu, Numan; Duman, Suayip Burak; Eser, Gozde; Topaloglu, Edanur; Ozemre, Begum
    Objective: The aim of this study was to evaluate periapical radiographs of enamel caries, dentin caries, and deep caries with exposed pulp and intact teeth obtained in vitro using photo-stimulated phosphor plates (PSP) under different exposure parameters. Methods: 3 non-carious extracted molars were selected. The obtained molars were embedded in the wax created from pink wax by ensuring approximal contact and a base was created. 14 different imaging protocols were used with 60 kVp, 4 mA 0.02-0.1 second and 70 kVp 7 mA, 0.25-1.25 second exposure parameters. Intact teeth were imaged with these various imaging protocols. Artificial cavities were then created for enamel caries, dentin caries and deep caries with exposed pulp and imaged according to the same protocols. The images were evaluated by 3 clinicians who were blind to the exposure protocol and caries status. Inter-observer agreement with actual situations was examined with Kappa statistics. Results: In the low-dose group, the kappa values of observer 1, observer 2, and observer 3 were 0.905, 0.952, 0.952, respectively. The kappa values of observer 1, observer 2, and observer 3 in the ultralow-dose group were 0.833, 1, 1, and the kappa values of observer 1, observer 2, and observer 3 in the high-dose group were 1, 1, 0.833, respectively. The results obtained in all groups showed a statistically significant-excellent agreement (p<0.001). Conclusion: Approximal caries can be diagnosed with intraoral radiography obtained with low radiation doses with PSP in dentistry. Thus, patients could be exposed to less ionizing radiation.
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    Nasopharynx evaluation in children of unilateral cleft palate patients and normal with cone beam computed tomography
    (Sage Publications Ltd, 2023) Temiz, Mustafa; Duman, Suayip Burak; Abdelkarim, Ahmed Z.; Bayrakdar, Ibrahim Sevki; Syed, Ali Z.; Eser, Gozde; Celik Ozen, Duygu
    Objective:This study aimed to examine the morphological characteristics of the nasopharynx in unilateral Cleft lip/palate (CL/P) children and non-cleft children using cone beam computed tomography (CBCT). Methods:A retrospective study consisted of 54 patients, of which 27 patients were unilateral CL/P, remaining 27 patients have no CL/P. Eustachian tubes orifice (ET), Rosenmuller fossa (RF) depth, presence of pharyngeal bursa (PB), the distance of posterior nasal spine (PNS)-pharynx posterior wall were quantitatively evaluated. Results:The main effect of the CL/P groups was found to be effective on RF depth-right (p < 0.001) and RF depth-left (p < 0.001). The interaction effect of gender and CL/P groups was not influential on measurements. The cleft-side main effect was found to be effective on RF depth-left (p < 0.001) and RF depth-right (p = 0002). There was no statistically significant relationship between CL/P groups and the presence of bursa pharyngea. Conclusions:Because it is the most common site of nasopharyngeal carcinoma (NPC), the anatomy of the nasopharynx should be well known in the early diagnosis of NPC.
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    Zygomaticocoronoid ankylosis with possible myositis ossificans: a very rare case
    (Springer, 2022) Eser, Gozde; Duman, Suayip Burak; Yolcu, Umit; Erdogan, Eren; Alan, Hilal
    Ankylosis forming between the zygomatic arch and the coronoid process is a rarely encountered pathological extracapsular ankylosis. Its treatment protocol consists of surgical removal of the coronoid process with the ankylotic mass and jaw opening-closing exercises after surgery. Myositis ossificans (MO) is a self-limiting, benign ossifying lesion. It affects all types of soft tissues including subcutaneous adipose tissue, muscles, tendons and nerves. It is most frequently found in the muscle as a solitary lesion. The clinical appearance of MO is generally in the form of a mass characterized with an ossified soft tissue. When it develops alone, cross-sectional imaging might not be specific, and it may appear similar to worse etiologies. It is suggested multiple imaging modalities should be used in the assessment of a suspicious soft tissue mass. MO is a benign self-limiting disease. In this case report, in the radiographic examination of a 41-year-old female patient, ankylosis between the left coronoid process and the zygomatic bone accompanied by possible MO in the left medial pterygoid muscle was observed. Resection of the coronoid process with the ipsilateral route, resection of the ankylotic mass with the hemicoronal approach and resection of the contralateral coronoid process with the intraoral approach were performed, but the ossified formation in the medial pterygoid muscle was not touched.