Automatic Blob Detection for Dental Caries

نویسندگان

چکیده

Dental Caries are one of the most prevalent chronic diseases around globe. Detecting carious lesions is a challenging task. Conventional computer aided diagnosis and detection methods in past have heavily relied on visual inspection teeth. These only effective large clearly visible caries affected been limited performance due to complex characteristics dental images, which consist hidden or inaccessible lesions. The early an important determinant for treatment benefits much from introduction new tools, such as radiography. In this paper, we propose deep learning-based technique namely: blob detection. proposed automatically detects bitewing radio-graphs. approach employs data augmentation increase number images set total 11,114 images. Image pre-processing was through use Gaussian blur filters. segmentation handled thresholding, erosion dilation morphology, while image boundary achieved active contours method. Furthermore, learning based network sequential model Keras extracts features Finally, convexity threshold value 0.9 introduced aid classification either present not present. process classifying results 97% 96% precision recall values, respectively.

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ژورنال

عنوان ژورنال: Applied sciences

سال: 2021

ISSN: ['2076-3417']

DOI: https://doi.org/10.3390/app11199232