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Three Dimensional Panorama Visualization for Endoscopic Video

机译:内窥镜视频的三维全景可视化

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Introduction: Endoscopy is widely used in the surgical world. Reduced surgical injury during endoscopic surgery makes the patient's life easy. However, the endoscopic surgery becomes a challenge for the novice surgeons because of the narrow field of view and the lack of 3D perception in the 2D endoscope image. Such limitations of the endoscope may be addressed with a 3D panorama created with the endoscopic 2D images. Few studies have been reported to create a 3D panorama from endoscopic images. However, to our knowledge, no study has reported a 3D panorama system which uses only a single camera image from the conventional endoscope to make a 3D shape of the organs, and further stitch those 3D shapes to create a 3D panorama of the surgical scene. Such system would enable surgeons to have an extended field of view of the surgical scene with a 3D perception. Method: Images from the endoscopic surgery video were used in this study. A shape from shading (SfS) algorithm was applied to create a 3D shape of the organs in the images. Characteristic feature points were identified on the images using a feature detection algorithm (SURF). The matching feature points in the consecutive images were found using a feature matching algorithm (BRIEF). An iterative closest point (TCP) algorithm was applied to stitch 3D shapes from the consecutive images to synthesize the 3D panorama. Results: The method was applied on 100 consecutive video frames from an endoscopic video of a patient. The root mean square error for the registration of the consecutive image feature points was <4 mm. The 3D panorama from the method helps in visualizing a larger area of the surgical anatomy. An improved version of the method may be applied to a real time video from the endoscope.
机译:简介:内窥镜检查广泛用于手术世界。在内窥镜手术期间减少手术损伤使患者的生活变得容易。然而,由于狭窄的视野和2D内窥镜图像中的3D感知,内窥镜手术成为新手外科医生的挑战。内窥镜的这种局限可以通过用内窥镜2D图像创建的3D全景来解决。据报道,很少有研究以从内窥镜图像创建3D全景。然而,对于我们的知识,没有研究报告了3D全景系统,该系统仅使用来自传统内窥镜的单个摄像机图像来制造器官的3D形状,并进一步缝合那些3D形状以创建外科人的3D全景。这种系统将使外科医生能够具有3D感知的外科场景的扩展视野。方法:在本研究中使用了内窥镜手术视频的图像。从阴影(SFS)算法的形状被应用于在图像中产生3D形状。使用特征检测算法(冲浪)在图像上识别特征特征点。使用特征匹配算法(简要)找到连续图像中的匹配特征点。迭代最接近点(TCP)算法应用于来自连续图像的针迹3D形状以合成3D全景。结果:从患者的内窥镜视频施加该方法。连续图像特征点的登记的根均方误差<4 mm。该方法的3D全景有助于可视化外科解剖结构的更大区域。该方法的改进版本可以应用于来自内窥镜的实时视频。

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