Teeth Disease Detection using Deep Learning

Registration ID: IJNRD_194815

Published ID: IJNRD2305407

DOI: Click Here to Get

Sanket Patil , Shubham Salunke , Pratiksha Yadav , Shejal Bendre , Aarti Pimpalkar

CNN; Medical Imaging; Image Processing; Machine Learning; Dental Informatics; X-Ray Semantic Segmentation.

Dentists use the panoramic dental X-ray images as a crucial diagnostic tool to identify symptoms early on and create effective treatment strategies. Deep learning techniques have been used in recent years to segment teeth in dental Xrays, helping dentists make clinical choices. The region-ofinterest (ROI), which should be the maxillofacial region, must be extracted from the original images because they are filled with a lot of unnecessary information. However, due to the poor image quality, a quick and precise maxillofacial segmentation without hand-crafted features is difficult. Here we use the teeth images for training and testing purposes to ease the process. In order to address this issue, we generate a sizable maxillofacial dateset and suggest an effective encoder-decoder network model called EED-Net. Keywords

Published Paper   E-Certificate

Sanket Patil, Shubham Salunke, Pratiksha Yadav, Shejal Bendre, & Aarti Pimpalkar (May-2023). Teeth Disease Detection using Deep Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), e58-e62. https://ijnrd.org/papers/IJNRD2305407.pdf

Volume 8 Issue 5, May-2023

Pages : e58-e62

Paper Reg. ID: IJNRD_194815

Published Paper Id: IJNRD2305407

Downloads: 000121979

Research Area: Engineering

Country: Pune, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305407.pdf

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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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