Odontoai
In this study, we used the "Odontoai" dataset to train and improve a YOLOv8‑seg model for efficient segmentation of dental radiographs. The dataset includes 52 distinct tooth categories (e.g., tooth‑11 to tooth‑85), with each image annotated by professional dentists. Standardized and verified annotations ensure high accuracy and consistency. The images cover diverse angles, lighting conditions, and backgrounds, enhancing model generalization. This high‑quality dataset enables the YOLOv8‑seg model to accurately identify and segment various tooth structures, supporting advanced dental diagnostics.
Description
牙片牙齿图像分割系统源码&数据集分享
数据集信息
数据集概述
- 数据集名称: Odontoai
- 数据集大小: 2000张牙齿图像
- 类别数: 52
- 类别名称:
- [tooth-11, tooth-12, tooth-13, tooth-14, tooth-15, tooth-16, tooth-17, tooth-18, tooth-21, tooth-22, tooth-23, tooth-24, tooth-25, tooth-26, tooth-27, tooth-28, tooth-31, tooth-32, tooth-33, tooth-34, tooth-35, tooth-36, tooth-37, tooth-38, tooth-41, tooth-42, tooth-43, tooth-44, tooth-45, tooth-46, tooth-47, tooth-48, tooth-51, tooth-52, tooth-53, tooth-54, tooth-55, tooth-61, tooth-62, tooth-63, tooth-64, tooth-65, tooth-71, tooth-72, tooth-73, tooth-74, tooth-75, tooth-81, tooth-82, tooth-83, tooth-84, tooth-85]
数据集构建
- 标准化和标注: 数据集经过严格的标准化和专业牙科医生的审核,确保标注的准确性和一致性。
- 图像多样性: 图像样本涵盖多种拍摄角度、光照条件和背景环境,增强模型的泛化能力。
数据集使用
- 数据划分: 数据集划分为训练集、验证集和测试集,用于模型的训练和评估。
- 应用场景: 数据集用于训练和改进YOLOv8-seg模型,实现牙片牙齿图像的高效分割。
研究背景与意义
- 应用领域: 计算机视觉在医疗领域的应用,特别是牙科图像处理。
- 研究目标: 开发高效的牙齿图像分割系统,提高牙科诊断和治疗的精准度。
- 技术优势: 基于改进的YOLOv8模型,具有高效的实时检测能力和较高的准确性。
系统功能
- 模型适配: 适配YOLOV8的“目标检测”模型和“实例分割”模型。
- 识别模式: 支持“图片识别”、“视频识别”、“摄像头实时识别”三种识别模式。
- 结果保存: 支持识别结果自动保存并导出到指定目录。
- Web前端: 支持Web前端系统中的标题、背景图等自定义修改。
数据集图片演示
- 图片展示:
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Topics
Source
Organization: github
Created: 10/18/2024
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