[IEEE 2013 3rd International Conference on Instrumentation, Communications, Information Technology,...

Quantitative Image Analysis of Periapical Dental Radiography for Dental Condition Diagnosis

Anita Ayuningtiyas1, Narendra Kurnia Putra2, Suprijanto2, Endang Juliastuti2, Lusi Epsilawati3

1Engineering Physics Program, Faculty of Industrial Technology, Institut Teknologi Bandung, Bandung, Indonesia2Instrumentation and Control Research Group, Faculty of Industrial Technology, Institut Teknologi Bandung, Bandung,Indonesia

3Department of Dental Radiology, Faculty of Dentistry, Padjadjaran University, Bandung, Indonesia(E-mail: [email protected])

Abstract—Periapical dental radiography have been used by the dentist to diagnose the lessions of the tooth. In Indonesia, recent development of this dental technology still used conventional method by using negative film with several limitation. This research was conducted to study digitalization of periapical film using digital dental X Ray reader for dental condition diagnosis.This dental condition was made by two step image analysis, consist of qualitative analysis and quantitative analysis the dentin and pulp. To segmen dentin and pulp, active contour was used to simplify the image analysis process. Qualitative analysis was made by the help of the visual inspection of the dentist, while quantitative analysis was made by compute various statistic parameter. Result of this research show that varians and the intensity ratio between dentin and pulp is good enough to be statistic parameter to differentiate the condition of the dental.

Keywords-periapical image, image segmentation, active contour, image analysis, statistical parameters

I. INTRODUCTION

The invention of X Ray in 1895 by Wilhelm Conrad Röntgen has brought the revolution an era of change in the medical field. Dentistry is one of the field, better known as dental radiology or dental radiographs. Radiographic examinations are one of the diagnostic tools used in densitry to determine level of the disease and the formula of the treatment. (Williamson, 2010) Dental radiographs that consist of two part, extra-oral and intra-oral, are very important tools to help the dentist diagnose the condition of the tooth. Film based and digital radiographics images are the devices required to maximize the diagnostic and interpretation of the dental condition while in the same time minimize the exposure the radiation to the patient. Imaging technique used film based still widely used in many country, while several country has switch to use digital radiographs. Indonesia is one of the country that still mostly used the film based because of the economical value.

Film based technique have several limitation as the doctorvision (qualitative analysis), image quality of the film, and the storage capacity. For overcome this limitation, the integration system developed betwen film based and digital technique which provide the quantitative analysis. This two type analysis ease the dentist to do the inspection and diagnosis and also reduce the X Ray exposure to the patient.

This research started by the digitalization process of the periapical film used the scanner. The final purpose is to find the statistic parameter which can be used to differentiate normal and inflammation tooth. To support this purpose, several process as segmentation (to divide dentin and pulp), pre-processing (to maximize the quality of the image), and histogram analysis are used.

Several problems appear when we tried to segment the tooth. In this research, we supposed to divide dentin and pulp into different part. In many dental images, gradient value between the teeth and background is similar, therefore, many segmentation method like threshold, gap valley, filtering are failure to extract or separate the contour. In [2], active contour model without edges is used to extract the contour of the teeth and had confirmed the efficacy of this technique. (Shah, Abaza, Ross, & Ammar, 2006) Hence, in this research , active contour is used to divide dentin and pulp. To improve the result, pre-processing technique is used to maximize the quality of the image.

II. METHODS

A. Image Analysis of Digital X Ray Periapical Radiography Periapical radiography describe the condition of the whole

tooth from root to crown. The expert dentist use their visual inspection to examine condition of the tooth. In this research, periapical film are digitized by dental x ray reader which work as a scanner. Digital periapical data then cropped by crop tool to determine region of interest (ROI) so the computation time is short enough. After that, pre – processing technique is applied to the region until the contrast optimal enough to be segment. This pre – processing technique applied by the help from the expert dentist to prevent contrast fault.

After the pre - processing, segmentation with active contour are applied to the tooth. This segmentation process are divide into two part. The first segmentation used to segment whole tooth from the background, and the second segmentation used to segment dentin with its pulp with image substraction technique. To show the differences between dentin and pulp, normalized histogram was appeared. Both dentin histogram and pulp histogram were showed some differences in statistic parameter. This process called quantitative analysis.

Quantitative analysis from normalized histogram both dentin and pulp are used to determine condition of normal and

2013 3rd International Conference on Instrumentation, Communications, Information Technology, and Biomedical Engineering (ICICI-BME)

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Bandung, November 7-8, 2013

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inflammation tooth. Several statistic parameter were calculated to show differences between these tooth by dentin and pulp character such as peak difference (Δp), intensity difference (ΔI), intensity ratio (d) and varians. Figure 1 showed the schematic process of this research.

Fig 1. Research Schematic Process

B. Image Samples SelectionEight dental image samples would be used on this research

which randomly selected and analyzed by the expert dentistinto different conditions and categorized as normal teeth or abnormal/inflammation teeth (Table 1).

Table 1. The Dental Samples Condition Sample Number Condition

1 Normal

2 Normal

3 Normal

4 Normal

5 Inflammation

6 Inflammation

7 Inflammation

8 Inflammation

C. Image Digitalization MethodThe common X Ray periapical image is preserved as film

which has static condition and cannot be processed to the further image analysis process. Thus, firstly the periapical film should be converted into a digital format. MD300 USB Digital Dental X Ray Reader packed with MD Image Software areused in the film scanning process in order to convert the film into a digital format. Digitalization process used to enlarge the capacity storage. Figure 2 showed the process of image digitalization.

Fig 2. Image Digitalization

D. Region of Interest and Segmentation ProcessPre – processing was used to maximize the quality of the

images, with light adjustment, similar with the concept of the viewer in dentistry. To segment the tooth from its baground, active contour was used. This method is based on the gradient equation and energy equalization. In this research, segmentation were divide into two part. First part was to divide a tooth from it background (which contain another tooth, etc), and the second step was to divide dentin with pulp. The inisialization curve determine the successfully condition of this segmentation part. When the curve were to far from the edge of the tooth, then the active contour process would took a long time and tended to be fail.

E. Parameters Comparison MethodTo validate the quantitative result based on statistic

parameters from the normalized histogram, the qualitative analysis was given from the expert dentist.

III. RESULTS AND DISCUSSIONS

A. Quantitative AnalysisQuantitative analysis was based on the normalize

histogram from each dentin and pulp. Figure 3 showed dentin and pulp of normal tooth and abnormal tooth. Several parameter such as peak difference (∆p), intensity difference (∆I), intensity comparison (d), and varians was calculated. The result oh this calculation were showed on Table 2.

(a) Normal Tooth

Periapical Film

Diffuser

Light From Diffuser

Camera Captured Image

Computer


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(b) Abnormal ToothFig 3. Normalized Histogram Dentin and Pulp

Table 2. Image Parameter(a) Peak

Data PDentin PPulp

1 184 119 65

2 154 142 12

3 145 137 8

4 62 35 27

5 138 96 42

6 127 184 57

7 177 157 20

8 161 12 149

(b) Intensity

Data Selisih

max min

1 76 11.7 3.1

2 49 8 2.1

3 76 7.7 1.9

4 42.2 19.2 1.4

5 92 61.5 2.3

6 4 7.9 1.1

7 11 68.5 2.3

8 20 3.8 1.2

(c) Varians

DataVarians

Dentin Pulp

1 0.112 0.059

2 0.056 0.032

3 0.073 0.059

4 0.061 0.098

5 0.076 0.093

6 0.060 0.035

7 0.076 0.040

8 0.077 0.043

B. Statistical ParametersFrom the result in part A, it showed the several parameter

calculation. From the normalized histogram, dentin describes in red bar and pulpa in blue bar. Statistic parameters were show that peak difference between dentin and pulp have a very wide range, thus could not diferentiate normal tooth and abnormal tooth. Intensity difference also show a similar result with before because it have very wide range between 4 – 92. However intensity comparison (d) and varians between dentin and pulp show some significant result. Normal tooth has larger d value but has smaller varians than abnormal tooth.

C. Results ComparisonFrom the quantitative result, we validate the data with help

from expert dentist or qualitative analysis. Dentist clarify that the normal tooth has a darker and narrow pulp than abnormal tooth.

IV. CONCLUSIONS

1. Digitalization process of periapical film using the periapical scanner produce digital periapical images. Contrast level of the digital images were adjustable.

2. Condition of the film depends on various factor, hence, not all the film can be digitilize.

3. Segmentation with active contour can effectively divide the tooth, dentin and pulp. Inizialization curve, image contrast, and resolution would become important role for the succes of the segmentation process.

4. Difference of peak (∆p) and intensity (∆I) not significantly show the characteristics of the normal and abnormal tooth. Comparison of the intensity (d), varians showed the significant result from the characteristics tooth condition.

ACKNOWLEDGMENT

The authors acknowledge with gratitude the great support of ASAHI Glass Foundation through the research grant program which supports this research activity.

REFERENCES

[1] Williamson, G. F. (2010). DENTSPLY Rinn. Retrieved June 23, 2013, from www.dentsplylearning.com

[2] Shah, S., Abaza, A., Ross, A., & Ammar, H. (2006). Automatic Tooth Segmentation Using Active Contour Without Edges. Biometric Symposium, 1.

[3] Whaites, Eric. “Essential of Dental Radiography and Radiology”.Churcill : Livingston, 2002.

[4] Gianto, “Study of Integration Medical System Panoramic Film Based and Digital Image for Visual Enhancement and Radiograph Analyze”,Thesis, Institut Teknologi Bandung, Bandung, 2010.

[5] Lusi Epsilawati, "Quantitative Analysis of Teeth Density," Dentistry Faculty, Universitas Padjajaran, Bandung, 2011.


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[6] Frederic H. Martini, “Fundamental of Anatomy and Physiology”, 7th ed., Leslie Berriman, Ed. San Francisco: Benjamin Cummings, 2006

[7] Affairs, American Dental Association Council on Scientific. 2006. “The Use of Dental Radiographs (Update and Recommendations)”, Chicago : American Dental Association, 2006.

[8] Said, Eyad Haj, Nassar, Diaa Eldin M. and Fahmy, Gamal, “Teeth Segmentation in Digitized Dental X - Ray Films

Using Mathematical Morphology”, 2006. 2, west Virginia :IEEE, 2006, Vol. 1. 1556-6013.

[9] Cheng, Jinyong and Sun, Xiaoyun, “Medical Image Segmentation with Improved Gradient Vector Flow”,2012. China : Maxwell Scientific Organization, 2012. 2040-7467.


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