3D modelling and x-ray depth analysis map of the pulp with computer software via digital periapical radiography and cone beam computed tomography

Abstract

Objective

Periapical radiographs (PAR) offer information about the pulp and periodontal health of teeth. However, intraoral radiographs are insufficient for diagnosing buccolingual anomalies and variations such as bifid canals due to their two-dimensional nature. Cone beam computed tomography (CBCT) is the gold standard for 3D imaging in the clinic but requires additional radiation. The aim of this study was to create a software (XPAR) which obtains x-ray depth analysis and 3D modelling of the pulps of single-rooted teeth by converting the grey values in the original radiographs into numerical data.

Materials and methods

Two single-rooted teeth were included in the experimental part of the study. Chicken fibula bone was preferred for alveolar bone simulation because it could simulate cortical and trabecular structures due to similarity. A total of four images (60kVp & 70kVp; single alveolar bone & double alveolar bone) were obtained. The aim of this experimental part is to test the repeatability and realism of the algorithm to be created for pulp modelling. Retrospectively, 31 single-rooted teeth with both periapical radiography and cone-beam computed tomography imaging were included in the retrospective part of the study. According to XPAR, depth increase areas were interpreted as root resorption and accessory canal. Depth decrease areas were evaluated as the transformation of the pulp from an elliptical to an oval form, pulp stone, bifid canal formation and the presence of thick alveolar bone. The diagnostic accuracy of XPAR application on pathological and morphological changes was evaluated by comparing the obtained results with CBCT.

Results

80% of the analyses diagnosed as bifurcation by XPAR application were supported by CBCT. This rate decreased to 27% in the diagnosis of transitions from elliptical to oval form. A total of 5 and 19 linear formations observed in the form of depth decrease and increase, respectively, were accepted as image errors in XPAR.

Conclusion

Buccolingual bifid canal formations and pulp obliterations can be diagnosed with a rate of nearly 50% with the depth decrease finding obtained in XPAR application. Imaging errors caused by deformed detectors are typically observed as linear formations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12903-025-05801-0.

Highlights

A software named XPAR was studied to perform x-ray depth analysis and 3D pulp modelling from radiographs.

XPAR software converts radiograph grey values into numerical data for 3D modelling.

Study tested two single-rooted teeth using chicken fibula for alveolar bone simulation.

XPAR showed 80% accuracy for bifurcation diagnosis compared to CBCT results.

XPAR diagnoses bifid canals and pulp obliterations with ∼ 50% accuracy; some image errors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12903-025-05801-0.

Introduction

Periapical radiographs (PAR) provide insight into the pulp, periapical status and periodontal health of teeth [1]. However, intraoral radiographs are inadequate in diagnosing buccolingual anomalies and variations such as bifid canals due to their two-dimensional nature [2]. The importance of pulp morphology, especially in terms of both endodontic treatments and age determination in orthodontics and forensic medicine, is increasing today, and alternatives to PAR are preferred in the examination of pulp morphology [3].

Cone beam computed tomography (CBCT) is a 3D diagnostic tool that overcomes the inherent limitations of 2D radiographic imaging, such as geometric distortion and overlapping of anatomical structures. This technique has been used in different population groups for various diagnostic purposes, such as root and canal anatomy definition, bifid canal detection, internal/external resorption detection, and hard tissue thickness measurement [4]. The detailed depiction of the 3D morphology of the pulp gives superiority to CBCT in contrast to PAR. However, there are also disadvantages of technique, such as cost and extra radiation exposure as compared to PAR [2, 5]. Micro-CT has higher image resolution than CBCT and is successful in showing accessory root canals and accessory foramina that cannot be detected by CBCT. The fact that it causes higher radiation exposure than CBCT is not considered a disadvantage because Micro-CT can be used in imaging ex-vivo materials [4].

Digital imaging systems in dentistry have developed rapidly in recent years, and especially with the increase in artificial intelligence applications. This provides faster and reliable interpretation of radiographic data [6, 7]. Increasing diagnostic success in dento-maxillofacial radiology has inevitably become a priority target with the use of new algorithms in digital dentistry. Intraoral radiographs become more functional with automatic caries detection using artificial intelligence applications [7]. PAR or bitewing radiographs can offer different diagnostic evaluation opportunities for clinicians with new algorithms that can be created.

Pseudo coloring applications are usually achieved by converting grey values into numerical data and allow for the classified presentation of grey values by collecting certain numerical values into the same colour group [8]. The limitation of the human eye in distinguishing shades of grey values is attempted to be compensated by pseudo coloring. Since the pulps of single-rooted teeth are exempt from root and anatomical landmark superpositions and their anatomical geometry is not complex, it is possible to perform depth analysis about the pulp based on x-ray transmittance behavior of tissues within the scope of pseudo coloring [2, 9]. After converting the grey values in PAR into numerical data, the difference between the high numerical data originating from the hard tissue around the pulp and the low numerical values in the pulp chamber can be theoretically used for pulp modelling using the background elimination method [9]. This is a novel method and has been tested theoretically with single-rooted teeth [9]. The reason for this is that the application will not give reliable results due to the superposition of multiple pulp cavities in multi-rooted teeth. Similarly, in the present study, single-rooted teeth, where the possibility of superposition is less, were preferred in order to reliably evaluate the pulp cavity.

Although CBCT is superior to PAR in endodontic diagnosis, it is not accepted as a routine practice to obtain CBCT in every case due to the radiation safety of the patients [4]. Therefore, clinicians have difficulty in determining the cases that require CBCT, especially due to the concern of unnecessary radiation exposure [4, 10]. This application, which can contribute to the ability of the human eye to distinguish gray tones, can make decision-making processes easier in 3D imaging diagnoses. This first study with this application based on digital algorithms can pave the way for the analysis of digital PAR images with artificial intelligence applications and the creation of advanced software that will provide diagnostic support to clinicians.

In the present study, it was aimed to obtain depth analysis and 3D modelling with an algorithm that was created using the findings obtained from previous pseudo coloring studies of the pulps of single-rooted teeth and planned to be presented as open access free software [9, 11, 12].

Materials and methods

Ethics approval

Ethics committee approval for this study was obtained from Karamanoglu Mehmetbey University Faculty of Medicine Local Scientific Medical Research Ethics Committee (06-2024/11). This study was conducted in accordance with the Declaration of Helsinki. The patients were informed and consent forms were obtained from the patients who agreed to participate in the study.

This study consists of two stages: ex-vivo experimental part and retrospective part. The ex-vivo experimental part was designed to observe to what extent the algorithm including the background elimination method on numerical data is affected by radiation exposure parameters and bone thickness. The aim of this experimental part is to observe how changes in exposure parameters and alveolar bone thickness cause changes in the obtained numerical data and to test the repeatability and realism of the algorithm to be created for pulp modelling. In the retrospective part, the consistency of the results of pulp depth analysis application was evaluated with CBCT data.

Ex-vivo experimental part

Two single-rooted teeth (mandibular incisor and mandibular premolar) extracted for various reasons were included in the experimental part of the study. The teeth were kept in 2% sodium hypochlorite solution for 24 h. Then, the teeth were washed with distilled water and positioned on a 5 × 10 cm dental wax plate so that their incisal and occlusal surfaces would touch the plate surface. Commercially available chicken fibula was preferred for alveolar bone simulation. The fibula was divided vertically into two equal parts and then divided horizontally again at a size close to the length of the tooth. In this way, four similar 2 mm thick alveolar bone simulation models were obtained. A socket was prepared on a wax plate at approximately 5 mm from the buccal and lingual surfaces of the teeth, into which bone simulation models for both teeth would be placed. Two exposure protocols, 60 kVp and 70 kVp, were determined for PAR imaging. PARs were taken with a wall-mounted periapical device (XMind DC, Satelec Acteon, France; 70kVp, 8 mA, 0.32 s) and a phosphor plate (Dürr Dental, Germany) and visualized with a phosphor plate scanner (VistaScan, Dürr Dental, Germany). The wax plate, teeth and x-ray tube were fixed to prevent changes in the numerical results due to such as angulation and distance (Fig. 1). Only the placement of alveolar bone simulators into prepared sockets was preferred as a variable parameter. Thus, a total of four images (60kVp & 70kVp; single alveolar bone & double alveolar bone) were obtained, allowing simultaneous PAR imaging of both teeth (Fig. 2). In order to standardise the manual pulp segmentation in the PAR images and to minimize the changes in numerical values caused by technical errors, the segmentation reference pixel coordinates were kept constant (Fig. 3).

Fig. 1.

Position of teeth with single alveolar bone simulation (a), position of teeth with double alveolar bone simulation (b), PAR exposure position (c)

Fig. 2.

PAR obtained with single alveolar bone simulation at 60 kVp (a), PAR obtained with single alveolar bone simulation at 70 kVp (b), PAR obtained with double alveolar bone simulation at 60 kVp (c), PAR obtained with double alveolar bone simulation at 70 kVp (d)

Fig. 3.

In the ex-vivo experimental part, the standard analysis area segmented from the premolar (a), the standard analysis area segmented from the incisor (b) on the PAR

Retrospective part

Retrospectively, 31 single-rooted teeth (presumed single-rooted by PAR) with both PAR and CBCT imaging were included in the retrospective part of the study. The pulp in the PAR image was manually segmented with the created software (XPAR) and buccolingual depth analysis was created. The obtained coloured analysis results were evaluated for each tooth by an oral and maxillofacial radiologist (SS) with 6 years of experience, blind to CBCT data. Depth increase areas were interpreted as root resorption, while depth decrease areas were evaluated as the transformation of the pulp from an elliptical to an oval form in the axial section, pulp stone, bifid canal formation area (bifurcation) in the buccolingual direction and the presence of thick alveolar bone. Retrospective CBCT data for each tooth were evaluated by other oral and maxillofacial radiologist (SO) with 6 years of experience, independent of the XPAR analysis results. The diagnostic accuracy of XPAR application on pathological and morphological changes was evaluated by comparing the obtained results. It was aimed to reduce the risk of bias in the study outcomes by preferring two different observers to interpret CBCT and PAR images with blind evaluation.

Creation of the XPAR algorithm & software

Following is the equation used for 3D pulp modelling from periapical radiography based on the x-ray transmittance behaviour of tissues:

Where:

Rij: Result matrix, represents the z-depth per pixel.

Bij: Pixel value at 𝑖-th row and 𝑗-th column,

Ai: Maximum pixel value in the 𝑖-th row.

The formula used for calculating the new value for each pixel involves several steps. First, for each row in the image, the maximum pixel value is found and denoted as Ai. This represents the highest pixel value in the i-th row. Next, for each pixel in the i-th row and j-th column, a complex value is calculated using a combination of two mathematical functions: a logarithmic term and a sine term. The logarithmic term is obtained by taking the square of the difference between Ai and Bij and adding 1 to ensure the argument is always positive. This term emphasizes larger differences. The sine term is calculated by taking the ratio of Bij to Ai and applying the sine function, scaled by π/2 to transform the ratio into a value between 0 and 1. This introduces a non-linear component and ensures smooth variation within the primary interval of the sine function. When the pixel value Bij equals the maximum value Ai in its row, the result is explicitly set to 1. This approach distinctly handles maximum values while applying a complex transformation to other pixel values, ensuring consistency and distinction in the formula.

The application consists of two stages. The first stage involves using a crop operation to identify the dental canal from the image. The Pillow library is utilized for opening, converting, masking, and cropping images. In the second stage, further processing and analysis are performed on the cropped images. In this stage, ‘numpy’ is used for scientific computations, pandas for data analysis and manipulation, ‘plotly’ for creating and visualizing interactive 2D and 3D graphs, and ‘scipy.ndimage’ for edge detection using the Sobel filter. The Tkinter library is used to create the user interface and manage user interactions. By integrating these libraries, users can load, crop, process, and analyse dental canal images, and save the results to Excel files.

Sobel filter operator

The application, the Sobel filter is used to detect edges. The Sobel filter uses two separate kernels to detect horizontal and vertical edges of an image. The image is first loaded and then converted to greyscale format. After defining the Sobel X and Sobel Y kernels, these kernels are applied to the image to detect horizontal and vertical edges. Finally, the edge magnitude is calculated and the resulting image is saved. These process steps are illustrated in the flowchart diagram (Fig. 4).

Fig. 4.

Flowchart diagram of Sober filter

Results

Results of ex-vivo experimental part

It was observed that the total numerical value obtained from ex-vivo PAR images decreased with both kVp and bone thickness increase in both teeth. Especially the increase in kVp caused a significant decrease in the numerical value. The increase in bone thickness caused a slight decrease in numerical values. In addition, a sudden decrease in depth was observed in the middle third of the incisor root region, and CBCT supported the buccolingual transformation of the root into a bifid canal in this region (Fig. 5). The finding that XPAR application is affected by the increase in bone thickness has revealed the necessity of the new algorithm (endo mode whose equation is given) added to XPAR application. In simple terms, this equation (endo mode) can prevent the pulp model obtained from PAR images from being affected by buccolingual bone thickness change and contribute to the detection of abnormal bone thickness. In other words, an attempt was made to eliminate the disadvantage created by high numerical values obtained from grey values in the background elimination in the basic modelling (basic mode) logic in the XPAR application through endo mode. According to present equation, the average of the numerical values obtained for each pixel can be used for depth assessment of the relevant tooth. It is also thought that the relationship between the “endo mode” value and the “basic mode” value can give an idea about abnormal changes in alveolar bone thickness.

Fig. 5.

(Upper) Graphical representation of numerical values obtained with XPAR in the ex-vivo experimental part, (a)(bottom left) depth decrease area in the root mid-region of the ex-vivo incisor (red circle), the contour plot shows the variables represented on three axes: the left side (root vertical length) corresponds to the y-axis, the lower side (root mesiodistal width) to the x-axis, and the right side (root bucco-palatal/lingual depth) to the z-axis, (b)(bottom right) CBCT image of the buccolingual bifurcation area of the ex-vivo incisor (red circle)

Results of retrospective part

The comparison of the diagnostic estimates of XPAR application with the CBCT results is shown in Table 1. 80% of the analyses diagnosed as bifurcation by XPAR application were supported by CBCT. This rate decreased to 27% in the diagnosis of transitions from elliptical to oval form. Considering the difficulties in distinguishing between bifid canal formation and changes in pulp form in the axial section with XPAR application, the prediction of canal obliteration and bifid canal formation with depth analysis findings is supported by CBCT with a rate of 43% (Fig. 6). In predicting pulp calcifications with XPAR a 40% success rate was observed. In two cases where it was thought that the alveolar bone might have expanded in the buccolingual direction, the expansion of the alveolar bone was confirmed by CBCT. Only 1 of 12 samples (8%) that were reported to have internal/external resorption with XPAR application was confirmed to have resorption with CBCT. A total of 5 and 19 linear formations observed in the form of depth decrease and increase, respectively, were accepted as image errors (deformed phosphor plate welded) in XPAR application. Since these formations were not found in CBCT images, comparison with the gold standard could not be made.

Table 1.

Comparative presentation of CBCT results with XPAR application

Order	Tooth no	Decrease in XPAR	Decrease in CBCT	Increase in XPAR	Increase in CBCT	Consensus on ↓	Consensus on ↑
1	12	-	-	1*	-	-	-
2	13	1 #	1 #	-	-	1 #	-
3	15	1α+1β	1α +1β	-	-	1α +1β	-
4	35	1 α	1 α	1*	-	1 α	-
5	11	1 α	-	1*+1θ	-	-	-
6	21	1 α	-	1*+1θ	-	-	-
7	11	1 β	1 α	1 θ	1 θ	-	1 θ
8	12	-	-	1*	-	-	-
9	45	1 α	-	-	-	-	-
10	42	-	-	-	-	-	-
11	43	1*+1α	-	-	-	-	-
12	44	1α +1β	-	-	-	-	-
13	13	2α +1	-	1 θ	-	-	-
14	15	1#+1β	1 #	-	-	1 #	-
15	43	1*+1γ	1 γ	3*	-	1 γ	-
16	44	1 γ	1 γ	3*	-	1 γ	-
17	11	Cancelled
18	15	1 #	1 #	-	-	1 #	-
19	23	1 #	1 α	-	-	-	-
20	23	1 β	1 β	1*+1θ	-	1 β	-
21	44	1 α	1 α	-	-	1 α	-
22	31	-	-	2 θ	-	-	-
23	32	-	-	1*	-	-	-
24	42	-	-	1*	-	-	-
25	23	-	-	2 + 1θ	-	-	-
26	22	-	-	-	-	-	-
27	11	-	-	1*	-	-	-
28	12	1 α	1 β	2 θ	-	-	-
29	21	-	-	1 θ	-	-	-
30	22	1*	1 β	-	-	-	-
31	31	1*	1 β	2*	-	-	-
32	32	1 #	1 #	1 θ	-	1 #	-
TOTAL 1		5 # +11 α +5 β +2 γ +5*	4 # +5 α +5 β +2 γ	12 θ +19*	1 θ	4 # +3 α +2 β +2 γ	1 θ
TOTAL 2		23	16	12	1	11	1

bifurcation: ^#, transition from elliptical to oval:^α, pulp stone/calcification:^β, thick alveolar bone:^γ, imaging artefact:*, internal/external root resorption:^θ, TOTAL 1: All subheadings together, TOTAL 2: All results except imaging artefacts

Fig. 6.

The initial level of depth decrease (red line) in the original radiograph (a) and XPAR application (b), The appearance of bifid canal formation in the CBCT axial section of the same tooth (red line) (c), The internal resorption (white line) in the CBCT coronal section of the same tooth (d) and the XPAR depth increase finding of the same resorption (red circle) (b)

Discussion

The decrease in the total numerical value obtained with the XPAR software as kVp increases can be explained by the increase in penetration ability of x-rays as their energy increases. As x-rays increase in energy, they are absorbed less in tissues and the penetration difference between tissues begins to disappear. Thus, x-rays become less sensitive to the density differences of the tissues they pass through and begin to penetrate each tissue in a similar way, which is expected according to the rules of radiation physics. The increase in the thickness of hard tissues causes a decrease in the penetration ability of x-rays used for imaging purposes, and in this case, this can be explained by the fact that x-rays with constant energy after a certain threshold thickness value lead to a constant grey value formation (at least for the human eye) [2]. In order to observe the effects of changes in alveolar bone thickness and kVp value, the “endo mode” algorithm has been added to the XPAR application. The data we obtained from the retrospective part of the study led to the development of the endo mode application. The regions with increased radiopacity in the periapical radiograph are made similar to the other regions of the imaging with this algorithm and a clearer limited analysis image is obtained compared to the “basic mode”. It may be more appropriate to interpret the results of the “endo mode” algorithm together with the “basic mode” findings rather than evaluating them alone. In addition to these two analysis modes, the XPAR application also has a 3D modelling feature, and users can observe the simulation of the pulp from every angle (Fig. 7) (Supplementary File-01).

Fig. 7.

Basic mode (a), endo mode (b) and 3D modelling (c) images of a tooth mapped with the XPAR application

The main types of coloured depth maps obtained from the pulp with the XPAR application are shown in Fig. 8. In the present study, it was observed that the findings obtained with depth decrease areas were more consistent than the depth increase findings comparison with original radiograph. Therefore, it can be said that XPAR application is more successful in detecting buccolingual bifid canal formations than in determining resorptions. Additionally, horizontally linear formations were detected in many samples and these formations are likely to be artifacts due to phosphor plate deformation [13]. These linear formations in XPAR analysis are expected to negatively affect pulp evaluation. It may be recommended not to use deformable detectors or to prefer “solid state” detectors that are more resistant to deformation than phosphor plates to overcome this problem [2, 14].

Fig. 8.

Schematic presentation of the main types of colour depth maps obtained from the pulp with the XPAR

It does not seem possible to estimate the pulp volume with XPAR application at present. Because there are many different factors such as kVp, x-ray tube vertical angulation variability and pulp homogeneity that affect the numerical data obtained with XPAR and therefore the depth analysis. The most important factor that makes it impossible to estimate pulp volume is the lack of concrete data about the depth in the buccolingual direction. However, applications based on the principle of combining repeated periapical radiographs taken from different angles, such as intraoral tomosynthesis systems, can provide data on the depth in the buccolingual direction [15, 16]. Therefore, combining XPAR application with tomosynthesis systems can be used to estimate pulp volume. The numerical data obtained in the present study were evaluated for each tooth in its own group (maxilla/mandible and premolar/canine/incisor) and the pulp volume and alveolar bone thickness were attempted to be interpreted. This method, which partially helps in obtaining information about the expansion of the alveolar bone, has led to the development of the “endo mode” algorithm. The reports of all samples analysed with XPAR and CBCT ex-vivo and retrospectively, the comments about the volume with numerical data, and the PAR and XPAR images of each sample can be accessed in Supplementary File-02.

The XPAR algorithm works by converting the grey values in the pixels into numerical data in the cells and then processing the cells over the rows. Therefore, uploading the pulp to be analysed into the XPAR application in the vertical position as much as possible may increase the compatibility of the results with the original radiograph. On the other hand, abnormal findings may occur in the analysis of teeth with mesial/distal dilacerations due to difficulties in completely vertical positioning of the pulp. Another suggestion that should be taken into consideration to increase the quality of the analyses to be performed with the XPAR application is to analyse the PAR images taken with digital intraoral systems in their original form without applying any brightness/contrast/filtration process. Because the XPAR application maps the x-rays passing through the pulp, and since the grey values in the digitally processed PAR images have been changed for various purposes, the XPAR results will also be affected [2, 17]. It should also be noted that the structure frequently described as “pulp” in this study is not the pulpal biological structures that cannot be visualized even with CBCT, but the pulp cavity bordered by dentin.

Today, CBCT is considered the gold standard in endodontic imaging. However, clinicians may remain hesitant in the indication of CBCT in endodontic procedures due to its difficulty of application, time-consuming nature, increased cost, and most importantly, the need for additional radiation [10]. XPAR can be useful in determining the necessity of more advanced techniques such as CBCT by making a preliminary assessment of anomalies or suspicious situations. The main contribution of XPAR is to make the need for CBCT use more targeted. For example, pathologies such as bifid canals or pulp obliterations can be predicted in advance with the gray value analysis provided by XPAR, and CBCT scans can be applied only in suspicious cases. XPAR can encourage the use of CBCT only in necessary cases by detecting anomalies such as bifid canals and pulp obliterations with the depth analysis obtained from periapical images. This reduces unnecessary CBCT scans and provides both a reduction in patient radiation and a cost-effective process for the clinic. The XPAR application is an accessible program that does not require additional radiation, is reproducible, easy to use, and compatible with all intraoral digital imaging systems. Pulp segmentation from periapical radiography is manual and the analysis performed after segmentation is objective as it is done entirely with the XPAR algorithm. In the future, XPAR can be integrated with artificial intelligence to ensure segmentation standardization among users.

It has not been clarified whether the pulpal enlargements observed with XPAR in the pulps are accessory canals. CBCT is inadequate in showing accessory canals and accessory foramen, and Micro-CT is preferred in showing accessory anatomical structures. The reason why CBCT was preferred over Micro-CT in the current study is that it would be a more appropriate comparison in terms of clinical practice [4]. In other words, it was aimed to show that anatomical variations that are inadequate for PAR and can be visualized with CBCT can be diagnosed with XPAR application. Using Micro-CT as the gold standard and evaluating the success of XPAR in diagnosing accessory canals and foramen can be the subject of another study that can be conducted in the future.

The presence of the second mesiobuccal (MB2) canal in molars affects the success of endodontic treatment. Detection of MB2 and morphological changes in molars with MB2 are evaluated with CBCT and micro-CT [18]. It is predicted that the software tested in this study will not provide acceptable results in multi-rooted teeth theoretically. However, the existence of studies evaluating the relationship between tooth dimensions and the presence of MB2 suggests that this software can provide an idea for MB2 diagnosis by evaluating the molar pulps with intraoral radiographs. In addition, previous publication [11] in which the theoretical idea of ​​this software was presented also attracts the attention of studies conducted in the fields of geology/archaeology [19] and parasitology [20] related to trabecular structures. In summary, the areas where the software in question can be used in relation to various radiographic imaging in dentistry (panoramic radiography, bitewing radiography, etc.) and various pathological conditions/anatomical variations (early caries, mandibular canal anatomy, etc.) and the benefits it can provide in branches of science other than dentistry can be revealed with future pilot studies that will test the software.

Conclusion

XPAR application can provide a different perspective to digital periapical radiographs. Bifid canal formations and pulp obliterations were diagnosed with approximately 50% depth reduction findings obtained with XPAR application. Imaging errors caused by deformed detectors are typically observed as linear formations. A new study can be planned with Micro-CT to show whether accessory canals and foramen are diagnosed with XPAR. XPAR can contribute to PAR image evaluation as an application that does not require additional radiation, is repeatable, and is compatible with all intraoral imaging systems.

Electronic supplementary material

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Abbreviations

CBCT

Cone beam computed tomography

kVp

Peak kilovoltage

mA

Milliampere

PAR

Periapical radiographs

Author contributions

T.F.: Conceptualization, Methodology, Resources, Formal analysis, Writing– original draft, S.S.: Project administration, Investigation, Visualization, Writing– original draft, S.O.: Formal analysis, Writing– original draft, K.C.: Supervision, Writing– review and editing.

Funding

No funding.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

Ethics committee approval for this study was obtained from Karamanoglu Mehmetbey University Faculty of Medicine Local Scientific Medical Research Ethics Committee (06-2024/11). This study was conducted in accordance with the Declaration of Helsinki. The patients were informed and consent forms were obtained from the patients who agreed to participate in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.