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首页> 外文会议>National Conference on Biomedical Engineering;International Iranian Conference on Biomedical Engineering >Semi-automatic 3-D pose estimation of laparoscopic tools to generate 3-D labeled database by developing a graphical user interface
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Semi-automatic 3-D pose estimation of laparoscopic tools to generate 3-D labeled database by developing a graphical user interface

机译：半自动3-D通过开发图形用户界面来生成3-D标记数据库的腹腔镜工具

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With medical science advancement in today's modern world, minimally invasive surgery (MIS) has many advantages over open surgery. Despite these advantages, this method also has problems that can be resolved with 3-D surgical tools pose estimation by using a graphical user interface (GUI) to generate a 3-D labeled database of minimally invasive surgery. Since surgery is a continuous act, we have to consider the tools' position in each frame of the surgery video to estimate the 3-D pose of the tools during the surgery correctly. Previous studies to find the tool's position have been based on recognizing the tool in the image and then estimating its position by different methods in two or three dimensions. Since each of these methods had errors, we looked to reduce the errors and find the 3D position corresponding to each tool semi-automatically and more accurately. To this end, we develop and design a graphical user interface that displays the surgical environment in three dimensions. We also design the 3-D models of the laparoscopic tools so that by registering them on the 2-D images of the tools during surgery, the instrument's position could be identified more accurately. To register 3-D models on 2-D images of them, we use pre-prepared data that identifies each type of tool and each part of it with a distinct color. Finally, we can find the tool's location in the image and its placement using the spatial averaging of the color of each tool and its components. Next, we intend to match the models we have simulated in a different environment to the 2-D images of the instruments by automatically recognizing the tool's type using the user's knowledge. At this point, according to the unique color of each tool and its components, as well as the coordinates of placement of these colors, we determine the location of the tool and the axis of the tool to determine the angle of the tool in two dimensions. Finally, we position the tool model on the image manually and see the percentage of similarity using Sum of Absolute Differences method. Besides, this adjustment becomes more accurate by automatic checking for the best percentage of similarity while the tool rotates around the third axis. In conclusion, this method can generate a labeled database, which would help us use more accurate methods (such as using neural networks) to find the 3-D pose of surgical tools.
机译：随着当今现代世界的医学推进，微创手术（MIS）在开放手术方面具有许多优势。尽管有这些优点，但这种方法还具有通过使用图形用户界面（GUI）的三维外科工具姿势估计来解决的问题，以生成3-D标记的微创手术数据库。由于手术是一种持续的行为，我们必须考虑手术视频的每一帧中的工具的位置，以便在手术中正确估计工具的3D姿势。以前的研究找到了刀具的位置是基于识别图像中的工具，然后通过两种或三维的不同方法估计其位置。由于这些方法中的每一种都有错误，因此我们期待减少错误并找到与每个工具的3D位置自动，更准确地找到对应的3D位置。为此，我们开发和设计一个图形用户界面，可在三维中显示外科环境。我们还设计了腹腔镜工具的三维型号，以便通过在手术期间将它们注册到工具的2-D图像上，可以更准确地识别仪器的位置。要在其中的2-D图像上注册3-D模型，我们使用预先准备的数据来标识每种类型的工具和它的每个部分都具有不同的颜色。最后，我们可以使用每个工具和其组件的颜色的空间平均找到图像中的工具位置及其放置。接下来，我们打算将我们在不同环境中模拟的模型与使用用户的知识自动识别工具的类型来匹配仪器的2-D图像。此时，根据每个工具的独特颜色及其组件，以及放置这些颜色的坐标，我们确定工具的位置和工具的轴线，以确定工具的两个尺寸。最后，我们手动将工具模型定位在图像上，并使用绝对差异方法的总和查看相似性的百分比。此外，通过自动检查刀具围绕第三轴旋转时，这种调整通过自动检查最佳相似百分比而变得更准确。总之，该方法可以生成标记的数据库，这将有助于我们使用更准确的方法（例如使用神经网络）来找到手术工具的三维姿势。

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