Dental X-Ray Annotation Project

I need a reliable specialist to add pixel-level labels to a set of localized dental X-rays. Each image must contain separate masks for the following anatomical or restorative classes: • Background • Bone • Tooth (including Enamel and Dentin) • Pulp • Canal • Caries • Restoration • Filling • Implant • RCT High-precision contours around Caries, Implant and Restoration areas are the top priority, with equally careful delineation of Pulp and Canal. Please work in the annotation platform of your choice—Labelbox, Supervisely, V7 Darwin, CVAT, or a comparable tool—and export the dataset in COCO JSON (instance segmentation) or YOLO-compatible polygon format. Deliverables 1. A folder of the original X-rays plus their corresponding segmentation files, organised by image ID. 2. A brief QA report that summarises inter-annotator checks or automated validation you employed to guarantee accuracy. All files will be reviewed against clinical ground truth, so consistency and clean class separation are essential. Let me know your estimated turnaround time and any past experience you have with dental radiograph annotation or similar medical imaging tasks.

Project ID: 40472654