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利用内窥镜视频进行组织三维重建的镜面反射去除

Specular Reflection Removal for 3D Reconstruction of Tissues using Endoscopy Videos.

作者信息

Emaduddin Muhammad, Halic Tansel, Demirel Doga, Bayrak Coskun, Arikatla Venkata S, De Suvranu

机构信息

Department of Computer Science and Engineering, Texas A&M University, College Station, Texas.

Intuitive Surgical, Peachtree Corners, Georgia.

出版信息

Proc IEEE Southeastcon. 2023 Apr;2023:246-252. doi: 10.1109/southeastcon51012.2023.10115137. Epub 2023 May 8.

Abstract

Endoscopy is widely employed for diagnostic examination of the interior of organs and body cavities and numerous surgical interventions. Still, the inability to correlate individual 2D images with 3D organ morphology limits its applications, especially in intra-operative planning and navigation, disease physiology, cancer surveillance, etc. As a result, most endoscopy videos, which carry enormous data potential, are used only for real-time guidance and are discarded after collection. We present a complete method for the 3D reconstruction of inner organs that suggests image extraction techniques from endoscopic videos and a novel image pre-processing technique to reconstruct and visualize a 3D model of organs from an endoscopic video. We use advanced computer vision methods and do not require any modifications to the clinical-grade endoscopy hardware. We have also formalized an image acquisition protocol through experimentation with a calibrated test bed. We validate the accuracy and robustness of our reconstruction using a test bed with known ground truth. Our method can significantly contribute to endoscopy-based diagnostic and surgical procedures using comprehensive tissue and tumor 3D visualization.

摘要

内窥镜检查广泛应用于器官内部和体腔的诊断检查以及众多外科手术。然而,无法将单个二维图像与三维器官形态相关联限制了其应用,特别是在术中规划和导航、疾病生理学、癌症监测等方面。因此,大多数具有巨大数据潜力的内窥镜视频仅用于实时指导,收集后即被丢弃。我们提出了一种用于内部器官三维重建的完整方法,该方法提出了从内窥镜视频中提取图像的技术以及一种新颖的图像预处理技术,以从内窥镜视频重建并可视化器官的三维模型。我们使用先进的计算机视觉方法,并且不需要对临床级内窥镜硬件进行任何修改。我们还通过使用校准测试台进行实验,制定了图像采集协议。我们使用具有已知真实情况的测试台验证了我们重建的准确性和鲁棒性。我们的方法可以通过全面的组织和肿瘤三维可视化,为基于内窥镜检查的诊断和外科手术做出重大贡献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f0e/10603791/f8e1a6234252/nihms-1938930-f0001.jpg

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