Datasets:

ibrahimhamamci
/

DENTEX

@@ -3,12 +3,16 @@ title: "DENTEX Dataset"
 license: cc-by-nc-sa-4.0
 ---
 Welcome to the official page of the DENTEX dateset, 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.
 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 information. The second set of data is also partially labeled but contains additional enumeration information along with the quadrant. The third data is fully labeled because it includes all quadrant-enumeration-diagnosis information for each abnormal tooth, and all participant algorithms will be benchmarked on the third data.
 <p align="center">
-  <img src="https://github.com/ibrahimethemhamamci/CT-CLIP/blob/main/figures/CT-RATE.png?raw=true" width="100%">
 </p>
 ## DENTEXT Dataset
@@ -26,18 +30,14 @@ To enable effective use of the FDI system, the dataset is hierarchically organiz
 The diagnosis class includes four specific categories: caries, deep caries, periapical lesions, and impacted teeth. An additional 1571 unlabeled X-rays are provided for pre-training.tientID_scanID_reconstructionID. For instance, "valid_53_a_1" indicates that this is a CT volume from the validation set, scan "a" from patient 53, and reconstruction 1 of scan "a". This naming convention applies to all files.
 <p align="center">
-  <img src="https://github.com/ibrahimethemhamamci/CT-CLIP/blob/main/figures/CT-RATE.png?raw=true" width="100%">
 </p>
 ## Annotation Protocol
 The DENTEX provides three hierarchically annotated datasets that facilitate various dental detection tasks: (1) quadrant-only for quadrant detection, (2) quadrant-enumeration for tooth detection, and (3) quadrant-enumeration-diagnosis for abnormal tooth detection. Although it may seem redundant to provide a quadrant detection dataset, it is crucial for utilizing the FDI Numbering System. The FDI system is a globally-used system that assigns each quadrant of the mouth a number from 1 through 4. The top right is 1, the top left is 2, the bottom left is 3, and the bottom right is 4. Then each of the eight teeth and each molar are numbered 1 through 8. The 1 starts at the front middle tooth, and the numbers rise the farther back we go. So for example, the back tooth on the lower left side would be 48 according to FDI notation, which means quadrant 4, number 8. Therefore, the quadrant segmentation dataset can significantly simplify the dental enumeration task, even though evaluations will be made only on the fully annotated third data.
-<p align="center">
-  <img src="https://github.com/ibrahimethemhamamci/CT-CLIP/blob/main/figures/CT-CLIP.png?raw=true" width="100%">
-</p>
 ## Data Split for Evaluation and Training
 The DENTEX 2023 dataset comprises three types of data: (a) partially annotated quadrant data, (b) partially annotated quadrant-enumeration data, and (c) fully annotated quadrant-enumeration-diagnosis data. The first two types of data are intended for training and development purposes, while the third type is used for training and evaluations.

 license: cc-by-nc-sa-4.0
 ---
+<p align="center">
+  <img src="https://huggingface.co/datasets/ibrahimhamamci/DENTEX/blob/main/figures/dentex.jpg" width="100%">
+</p>
 Welcome to the official page of the DENTEX dateset, 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.
 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 information. The second set of data is also partially labeled but contains additional enumeration information along with the quadrant. The third data is fully labeled because it includes all quadrant-enumeration-diagnosis information for each abnormal tooth, and all participant algorithms will be benchmarked on the third data.
 <p align="center">
+  <img src="https://huggingface.co/datasets/ibrahimhamamci/DENTEX/blob/main/figures/output.png" width="100%">
 </p>
 ## DENTEXT Dataset
 The diagnosis class includes four specific categories: caries, deep caries, periapical lesions, and impacted teeth. An additional 1571 unlabeled X-rays are provided for pre-training.tientID_scanID_reconstructionID. For instance, "valid_53_a_1" indicates that this is a CT volume from the validation set, scan "a" from patient 53, and reconstruction 1 of scan "a". This naming convention applies to all files.
 <p align="center">
+  <img src="https://huggingface.co/datasets/ibrahimhamamci/DENTEX/blob/main/figures/data.png" width="100%">
 </p>
 ## Annotation Protocol
 The DENTEX provides three hierarchically annotated datasets that facilitate various dental detection tasks: (1) quadrant-only for quadrant detection, (2) quadrant-enumeration for tooth detection, and (3) quadrant-enumeration-diagnosis for abnormal tooth detection. Although it may seem redundant to provide a quadrant detection dataset, it is crucial for utilizing the FDI Numbering System. The FDI system is a globally-used system that assigns each quadrant of the mouth a number from 1 through 4. The top right is 1, the top left is 2, the bottom left is 3, and the bottom right is 4. Then each of the eight teeth and each molar are numbered 1 through 8. The 1 starts at the front middle tooth, and the numbers rise the farther back we go. So for example, the back tooth on the lower left side would be 48 according to FDI notation, which means quadrant 4, number 8. Therefore, the quadrant segmentation dataset can significantly simplify the dental enumeration task, even though evaluations will be made only on the fully annotated third data.
 ## Data Split for Evaluation and Training
 The DENTEX 2023 dataset comprises three types of data: (a) partially annotated quadrant data, (b) partially annotated quadrant-enumeration data, and (c) fully annotated quadrant-enumeration-diagnosis data. The first two types of data are intended for training and development purposes, while the third type is used for training and evaluations.