超级模型:测试医学成像技术的先进模型

Srirang Manohar, Ioannis Sechopoulos, Mark A. Anastasio, Lena Maier-Hein, Rajiv (Raj) Gupta
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引用次数: 0

摘要

模型是用于医学成像技术初始测试和优化的测试对象,但这些模型很少能捕捉到组织的复杂特性。我们在此介绍超级模型,它超越了标准模型,能够复制组织和器官的复杂解剖和功能成像特性。这些超级模型可以是计算机模型、无生命的实物或活体器官。在这些超级模型上进行测试,可以在体内研究之前进行迭代改进,从而促进创新。我们将举例说明超级模型,解决开发过程中遇到的挑战,并设想由中央设施支持多个机构将这些模型应用于医学进步。在这篇《视角》中,马诺哈尔及其同事介绍了超级模型,作为数字或物理模型,超级模型能够模拟成像方法的复杂组织特征。他们讨论了模型对于测试新成像技术的重要性,并探讨了围绕模型开发和实施的关键问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Super phantoms: advanced models for testing medical imaging technologies

Super phantoms: advanced models for testing medical imaging technologies
Phantoms are test objects used for initial testing and optimization of medical imaging techniques, but these rarely capture the complex properties of the tissue. Here we introduce super phantoms, that surpass standard phantoms being able to replicate complex anatomic and functional imaging properties of tissues and organs. These super phantoms can be computer models, inanimate physical objects, or ex-vivo organs. Testing on these super phantoms, will enable iterative improvements well before in-vivo studies, fostering innovation. We illustrate super phantom examples, address development challenges, and envision centralized facilities supporting multiple institutions in applying these models for medical advancements. In this Perspective, Manohar and colleagues introduce super phantoms as digital or physical models capable of mimicking complex tissue characteristics for imaging methods. They discuss phantoms as crucial for testing of new imaging technologies, and address critical issues surrounding their development and implementation.
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