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An interactive medical image segmentation system based on the optimal management of regions of interest using topological medical knowledge

机译:基于拓扑医学知识的感兴趣区域最优管理的交互式医学图像分割系统

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摘要

This paper presents an original interactive system for efficient medical image segmentation in computer aided diagnosis. The main originality concerns the method used to manage, according to an a priori topological-based structural model, regions of interest (ROIs) within which computations can be constrained. The goal is then to avoid the processing of irrelevant image points, therefore improving and accelerating segmentations. In the case of a hierarchical modeling procedure, our ROI management method enables, for delineating a given medical structure, to optimally determine image points of interest by taking previously segmented structures into account. We propose a mathematical formulation of the method as well as a possible implementation within an interactive system. We also detail an experience report focussing on the segmentation of several abdominal structures from a CT image. It illustrates the behavior and the potential of our method.
机译:本文提出了一种原始的交互式系统,可以在计算机辅助诊断中进行有效的医学图像分割。主要创意涉及一种方法,该方法用于根据基于先验拓扑的结构模型来管理感兴趣的区域(ROI),在其中可以限制计算。然后,目标是避免处理无关的图像点,从而改善和加速分割。在采用分层建模程序的情况下,我们的ROI管理方法可以通过描述先前分割的结构来描绘给定的医疗结构,从而最佳地确定感兴趣的图像点。我们提出该方法的数学公式以及在交互式系统中的可能实现。我们还将详细介绍一份经验报告,重点是从CT图像中分割几个腹部结构。它说明了我们方法的行为和潜力。

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