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Welcome to the official page of the DENTEX dataset, which has been released as part of the [Dental Enumeration and Diagnosis on Panoramic X-rays Challenge (DENTEX)](https://dentex.grand-challenge.org/), organized in conjunction with the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) in 2023. The primary objective of this challenge is to develop algorithms that can accurately detect abnormal teeth with dental enumeration and associated diagnosis. This not only aids in accurate treatment planning but also helps practitioners carry out procedures with a low margin of error.
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The challenge provides three types of hierarchically annotated data and additional unlabeled X-rays for optional pre-training. The annotation of the data is structured using the Fédération Dentaire Internationale (FDI) system. The first set of data is partially labeled because it only includes quadrant info. The second set of data is also partially labeled but contains additional enumeration information along with the quadrant. The third set is fully labeled because it includes all quadrant-enumeration-diagnosis information for each abnormal tooth, and all participant algorithms have been benchmarked on this third set, with an example output shown below.
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## DENTEX Dataset
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<img src="https://huggingface.co/datasets/ibrahimhamamci/DENTEX/resolve/main/figures/dentex.jpg?download=true" width="100%">
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Welcome to the official page of the DENTEX dataset, which has been released as part of the [Dental Enumeration and Diagnosis on Panoramic X-rays Challenge (DENTEX)](https://dentex.grand-challenge.org/), organized in conjunction with the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) in 2023. The primary objective of this challenge is to develop algorithms that can accurately detect abnormal teeth with dental enumeration and associated diagnosis. This not only aids in accurate treatment planning but also helps practitioners carry out procedures with a low margin of error.
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The challenge provides three types of hierarchically annotated data and additional unlabeled X-rays for optional pre-training. The annotation of the data is structured using the Fédération Dentaire Internationale (FDI) system. The first set of data is partially labeled because it only includes quadrant info. The second set of data is also partially labeled but contains additional enumeration information along with the quadrant. The third set is fully labeled because it includes all quadrant-enumeration-diagnosis information for each abnormal tooth, and all participant algorithms have been benchmarked on this third set, with an example output shown below.
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<p align="center">
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<img src="https://huggingface.co/datasets/ibrahimhamamci/DENTEX/resolve/main/figures/output.png?download=true" width="100%">
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</p>
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## DENTEX Dataset
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