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Medical computer vision, virtual reality and robotics

机译:医用计算机视觉,虚拟现实和机器人技术

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摘要

The automated analysis of 3D medical images can improve both diagnosis and therapy significantly. This automation raises a number of new fascinating research problems in the fields of computer vision, graphics and robotics. In this paper, I propose a list of such problems after a review of the current major 3D imaging modalities, and a description of the related medical needs. I then present some of the past and current work done in our research group EPIDAURE at INRIA, on the following topics: segmentation of 3D images; 3D shape modelling; 3D rigid and nonrigid registration; 3D motion analysis; and 3D simulation of therapy. Most topics are discussed in a synthetic manner, and illustrated by results. Rigid matching is treated more thoroughly as an illustration of a transfer from computer vision towards 3D image processing. The later topics are illustrated by preliminary results, and a number of promising research tracks are suggested.
机译:3D医学图像的自动分析可以显着改善诊断和治疗。这种自动化在计算机视觉,图形和机器人技术领域提出了许多新的有趣的研究问题。在本文中,我在回顾了当前主要的3D成像方式之后,提出了此类问题的清单,并描述了相关的医疗需求。然后,我将介绍INRIA的EPIDAURE研究小组在过去和现在所做的一些工作,涉及以下主题:3D图像分割; 3D形状建模; 3D刚性和非刚性配准; 3D运动分析;和治疗的3D模拟。大多数主题以综合方式进行讨论,并通过结果进行说明。刚性匹配被更彻底地视为从计算机视觉到3D图像处理的转移。初步的结果说明了后面的主题,并提出了许多有前途的研究方向。

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