医学图像变化检测的微分几何方法

Alexander Naitsat, Emil Saucan, Y. Zeevi
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引用次数: 4

摘要

变化检测在医学成像中至关重要,是一种非侵入性的、可量化的肿瘤诊断和治疗效果评估的有力工具。我们提出了一种新的定量方法,用于检测体积医学数据和解剖结构聚类的变化,该方法基于对体积畸变的评估,这些畸变是为了将测试三维医学数据集片段变形到其先前获得的参考或案例聚类中的给定原型上所必需的。与基于体素的经典形状比较技术不同,我们的算法在四面体网格上运行,因此可以应用于封闭、单连通的表面和具有更复杂边界的体积域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Differential Geometry Approach for Change Detection in Medical Images
Change detection is of paramount importance in medical imaging, serving as a non-invasive quantifiable powerful tool in diagnosis and in assessment of the outcome of treatment of tumors. We present a new quantitative method for detecting changes in volumetric medical data and in clustering of anatomical structures, based on assessment of volumetric distortions that are required in order to deform a test three-dimensional medical dataset segment onto its previously-acquired reference, or a given prototype in the case clustering. Unlike the voxel-based classical techniques of shape comparison, our algorithm operates on tetrahedral meshes and can, therefore be applied on both closed, simply-connected, surfaces and in volumetric domains with more sophisticated boundaries.
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