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DETDet: Dual Ensemble Teeth Detection

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arxiv 2308.14070 v1 pith:HPDQU4AL submitted 2023-08-27 cs.CV

DETDet: Dual Ensemble Teeth Detection

classification cs.CV
keywords detdetdiagnosisensembleenumerationmoduleteethdatadental
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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The field of dentistry is in the era of digital transformation. Particularly, artificial intelligence is anticipated to play a significant role in digital dentistry. AI holds the potential to significantly assist dental practitioners and elevate diagnostic accuracy. In alignment with this vision, the 2023 MICCAI DENTEX challenge aims to enhance the performance of dental panoramic X-ray diagnosis and enumeration through technological advancement. In response, we introduce DETDet, a Dual Ensemble Teeth Detection network. DETDet encompasses two distinct modules dedicated to enumeration and diagnosis. Leveraging the advantages of teeth mask data, we employ Mask-RCNN for the enumeration module. For the diagnosis module, we adopt an ensemble model comprising DiffusionDet and DINO. To further enhance precision scores, we integrate a complementary module to harness the potential of unlabeled data. The code for our approach will be made accessible at https://github.com/Bestever-choi/Evident

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