Developing a Novel Approach for Periapical Dental Radiographs Segmentation
Image processing techniques has been widely used in dental researches such as human identification and forensic dentistry, teeth numbering, dental carries detection and periodontal disease analysis. One of the most challenging parts in dental imaging is teeth segmentation and how to separate them from each other. In this paper, an automated method for teeth segmentation of Periapical dental x-ray images which contain at least one root-canalled tooth is proposed. The result of this approach can be used as an initial step in bone lesion detection. The proposed algorithm is made of two stages. The first stage is pre-processing. The second and main part of this algorithm calculated rotation degree and uses the integral projection method for tooth isolation. Experimental results show that this algorithm is robust and achieves high accuracy.
Code (0)
등록된 구현이 없습니다.
Tasks
Lesion DetectionSegmentationSimilar Papers 제목 키워드 기반
PRAD: Periapical Radiograph Analysis Dataset and Benchmark Model Development
Deep learning (DL), a pivotal technology in artificial intelligence, has recently gained substantial traction in the domain of dental auxiliary diagnosis. However, its application has predominantly been confined to imagi…
Image SegmentationMedical Image SegmentationSemantic SegmentationDental CLAIRES: Contrastive LAnguage Image REtrieval Search for Dental Research
Learning about diagnostic features and related clinical information from dental radiographs is important for dental research. However, the lack of expert-annotated data and convenient search tools poses challenges. Our p…
DiagnosticImage RetrievalRepresentation LearningRetrievalArtificial Intelligence to Assess Dental Findings from Panoramic Radiographs -- A Multinational Study
Dental panoramic radiographs (DPRs) are widely used in clinical practice for comprehensive oral assessment but present challenges due to overlapping structures and time constraints in interpretation. This study aimed to …
DiagnosticSemantic SegmentationSensitivitySpecificityRadious: Unveiling the Enigma of Dental Radiology with BEIT Adaptor and Mask2Former in Semantic Segmentation
X-ray images are the first steps for diagnosing and further treating dental problems. So, early diagnosis prevents the development and increase of oral and dental diseases. In this paper, we developed a semantic segmenta…
Image SegmentationSegmentationSemantic SegmentationSelf-Supervised Learning with Masked Image Modeling for Teeth Numbering, Detection of Dental Restorations, and Instance Segmentation in Dental Panoramic Radiographs
The computer-assisted radiologic informative report is currently emerging in dental practice to facilitate dental care and reduce time consumption in manual panoramic radiographic interpretation. However, the amount of d…
Instance SegmentationSelf-Supervised LearningSemantic Segmentation