Identification of molar and premolar teeth in dental panoramic radiograph image

Rahmat, R F; Silviani, Silviani; Nababan, Erna Budhiarti; Sitompul, Opim Salim; Anugrahwaty, Rina; Silmi, Silmi

doi:10.1109/iac.2017.8280614

Cited by 4 publications

(3 citation statements)

References 14 publications

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“…In general, edge detection algorithms are applied to extract regions of interest but the accuracy is not well defined, which can be resolved by the snake-based approach. The snakebased approach used in the paper segregates the original image into several sub-images in such a way that it satisfies the appropriate conditions [4].…”

Section: Literature Reviewmentioning

confidence: 99%

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Multi-orientation local ternary pattern-based feature extraction for forensic dentistry

Rajmohan¹,

Khader²

2022

J Image Video Proc.

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Accurate and automated identification of the deceased victims with dental radiographs plays a significant role in forensic dentistry. The image processing techniques such as segmentation and feature extraction play a crucial role in image retrieval in accordance with the matching image. The raw image undergoes segmentation, feature extraction and distance-based image retrieval. The ultimate goal of the proposed work is the automated quality enhancement of the image by providing advanced enhancement techniques, segmentation techniques, feature extraction, and matching techniques. In this paper, multi-orientation local ternary pattern-based feature extraction is proposed for feature extraction. The grey level difference method (GLDM) is adopted to extract the texture and shape features that are considered for better results. The image retrieval is done by the computation of similarity score using distances such as Manhattan, Euclidean, vector cosine angle, and histogram intersection distance to obtain the optimal match from the database. The manually picked dataset of 200 images is considered for performance analysis. By extracting both the shape features and texture features, the proposed approach achieved maximum accuracy, precision, recall, F-measure, sensitivity, and specificity and lower false-positive and negative values.

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Section: Literature Reviewmentioning

confidence: 99%

“…The dental records obtained after post-mortem are in the form of radiograph images, panoramic images, bitewing images, or periapical images [3]. The images are compared and identified by the general image processing steps that include preprocessing, image enhancement, image segmentation, feature extraction, and classification [4].…”

mentioning

confidence: 99%

Multi-orientation local ternary pattern-based feature extraction for forensic dentistry

Rajmohan¹,

Khader²

2022

J Image Video Proc.

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“…In an effort to examine the use of teeth to estimate height 11 , researchers from outside Indonesia, have conducted several studies using a variety of method using tooth dimensions as parameters (odontometric parameters), both using permanent maxillary teeth 5,[12][13][14][15] , permanent mandibular teeth 9,10,16,17 , as well as a combination of maxillary and mandibular permanent teeth 18 , some have even examined using deciduous teeth 19 . Odontometric parameters that have been used include tooth length, crown length, mesiodistal width, labiolingual/buccolingual width, and relationship to facial measurements.…”

Section: Introductionmentioning

confidence: 99%

Successful Rate of Stature Estimation Using Odontometric Parameter with Carrea’s Index in Mongoloid Population

2020

MLU

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Background: Stature estimation is one of the four pillars in the anthropological identification protocol. During this time, stature estimation uses long bones, but if no long bones are found, tooth dimensions begin to be examined as a tool in stature estimation.Purpose: The aim of this study was to be able to determine the percentage of success in using tooth dimensions to estimate height in the Mongoloid population in Indonesia, using the Carrea's Index method.Method: The study was carried out by measuring the dimensions of arch and chord, then put into the Carrea formula, the results were compared with actual height, then calculated the frequency of predictions of success and non-success, compared to gender, and quadrant side of jaw.Results: The results of predictions of success for both women and men on both sides of the mandibular were a successful prediction of 69.6% and a non-successful prediction of 30.4%. In each sex, the success rate was different for each side, without a statistically significant difference (right p value 0.186; left p value 0.713) using Chi-square test. The results of the Pearson Correlation Coefficient test have a positive correlation (p <0.05) indicating that there is a significant relationship between height and the results of height estimation obtained from tooth dimension measurements. Conclusion:Based on the successful rate of the Carrea's Index method in this study shows that the Carrea's Index method can be used in the Mongoloid population in Indonesia as a tool for human identification.

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Adaptive Moment Estimation To Minimize Square Error In Backpropagation Algorithm

Singarimbun

Nababan

Sitompul

2019

2019 International Conference of Computer Science and Information Technology (ICoSNIKOM)

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Identification of molar and premolar teeth in dental panoramic radiograph image

Cited by 4 publications

References 14 publications

Multi-orientation local ternary pattern-based feature extraction for forensic dentistry

Multi-orientation local ternary pattern-based feature extraction for forensic dentistry

Successful Rate of Stature Estimation Using Odontometric Parameter with Carrea’s Index in Mongoloid Population

Adaptive Moment Estimation To Minimize Square Error In Backpropagation Algorithm

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