Suppr超能文献

基于 CNN-Transformer 分割的轮廓多视图的长骨三维重建方法。

A 3D reconstruction method based on multi-views of contours segmented with CNN-transformer for long bones.

机构信息

School of Mechanical Engineering, Tongji University, Shanghai, 201804, China.

Department of Orthopaedics, The First People's Hospital of Yancheng, Yancheng Jiangsu, 224300, China.

出版信息

Int J Comput Assist Radiol Surg. 2022 Oct;17(10):1891-1902. doi: 10.1007/s11548-022-02701-4. Epub 2022 Jul 19.

Abstract

PURPOSE

In computer-assisted diagnosis for orthopedic treatment, 3D reconstruction of bones is critical. Traditional 3D imaging technologies like CT and MRI have been proposed, but their high radiation dose and the requirements for lying postures could impact the accuracy of reconstructed bones and diagnosis results. Meanwhile, methods based on bone contours always depend on prior knowledge and lack precise bone segmentation methods. To address these issues, a bone reconstruction method based on multi-views of contours is proposed, as well as a hybrid CNN-Transformer approach for bone contours segmentation.

METHODS

A four-step strategy is introduced including segmenting bone contours from X-ray images, calculating 3D sparse, dense point clouds based on contours, and reconstructing surface. The Trans-DetSeg approach for interest regions detection and bone segmentation is proposed for accurate contours. Besides, the mathematical description of mapping relationships between contours in different views of X-ray images is provided. Then, bone sparse and dense point clouds are generated subsequently. Based on dense point clouds and the power crust method, realistic bone models are reconstructed.

RESULTS

Evaluated on 301 bone X-ray images and by considering p-value < 0.05, the proposed Trans-Detseg approach performed better with Dice Similarity Coefficient of 0.949 and Hausdorff Distance of 26.17 than three state-of-the-art models. Furthermore, the accuracy of the bone 3D reconstruction was investigated in three tibia cases and the proposed method was verified based on comparisons of results and CT data. It was proved that increased views of X-ray images could reduce the Average Surface Distance and perfect the structure information of reconstructed bones.

CONCLUSION

A new method for bone 3D reconstruction based on segmented bone contours on multi-views of X-ray images has been developed. Besides, a hybrid CNN-Transformer approach is introduced to segment bone contours. Evaluations proved the efficiency and accuracy of the proposed bone 3D reconstruction method.

摘要

目的

在骨科治疗的计算机辅助诊断中,骨骼的 3D 重建至关重要。已经提出了传统的 3D 成像技术,如 CT 和 MRI,但它们的辐射剂量高,且对躺卧姿势的要求可能会影响重建骨骼和诊断结果的准确性。同时,基于骨轮廓的方法总是依赖于先验知识,并且缺乏精确的骨分割方法。为了解决这些问题,提出了一种基于多视图轮廓的骨重建方法,以及一种用于骨轮廓分割的混合 CNN-Transformer 方法。

方法

介绍了包括从 X 射线图像中分割骨轮廓、基于轮廓计算 3D 稀疏、密集点云和重建表面的四步策略。提出了 Trans-DetSeg 方法用于感兴趣区域检测和精确的轮廓分割。此外,还提供了 X 射线图像不同视图中轮廓之间映射关系的数学描述。然后,生成骨稀疏和密集点云。基于密集点云和功率壳方法,重建真实的骨骼模型。

结果

在 301 张骨骼 X 射线图像上进行评估,并考虑 p 值<0.05,所提出的 Trans-Detseg 方法的 Dice 相似系数为 0.949,Hausdorff 距离为 26.17,优于三种最先进的模型。此外,还研究了三种胫骨病例的骨骼 3D 重建准确性,并基于结果和 CT 数据的比较验证了所提出方法的有效性。结果表明,增加 X 射线图像的视图可以减少平均表面距离并完善重建骨骼的结构信息。

结论

已经开发了一种新的基于 X 射线图像多视图分割骨轮廓的骨骼 3D 重建方法。此外,还引入了一种混合 CNN-Transformer 方法来分割骨轮廓。评估结果证明了所提出的骨骼 3D 重建方法的效率和准确性。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验