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OII-DS: A benchmark Oral Implant Image Dataset for object detection and image classification evaluation
Qianqing Nie1, Chen Li1, Jinzhu Yang2
1Microscopic Image and Medical Image Analysis Group, College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China; Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang, Liaoning, China.
Researchers developed the Oral Implant Image Dataset (OII-DS), a large collection of oral CT and implant images. This benchmark dataset supports advancements in dental image analysis for object detection and classification.
Area of Science:
- Dentistry
- Medical Imaging
- Computer Vision
Background:
- Increasing reliance on image analysis in dentistry for tasks like classification and object detection.
- Limited availability of benchmark datasets hinders research and development in this field.
Purpose of the Study:
- To introduce and validate the Oral Implant Image Dataset (OII-DS), a novel benchmark dataset.
- To support research in oral image analysis, specifically for object detection and image classification tasks.
Main Methods:
- Compiled OII-DS with 3834 oral CT images and 15240 oral implant images.
- Evaluated object detection using five algorithms and four criteria, with mean average precision for multi-object detection.
- Assessed image classification with 13 classifiers across five categories, using four evaluation criteria.
Main Results:
- Experimental results confirm the high quality and suitability of the OII-DS.
- The dataset effectively supports the evaluation of object detection and image classification methods.
- Demonstrated the dataset's validity through rigorous testing of established algorithms.
Conclusions:
- The Oral Implant Image Dataset (OII-DS) is a valuable, high-quality resource for dental image analysis research.
- OII-DS is openly available for non-commercial use, promoting further investigation in the domain.
- The dataset facilitates the development and benchmarking of advanced image analysis techniques in dentistry.
