三维多模态医学图像分割技术及软件工具

Deshan Yang, Jie Zheng, Ahmad Nofal, J. Deasy, I. E. Naqa
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引用次数: 21

摘要

在无创诊断放射学和图像引导放射治疗的时代,人们对应用不同的成像方式来分期和定位复杂疾病(如动脉粥样硬化或癌症)的兴趣日益浓厚。已经观察到,使用来自多模态图像的互补信息通常可以显着提高放射治疗癌症靶体积定义的鲁棒性和准确性。在这项工作中,我们提出了技术和一个交互式软件工具来支持这种3D多模态医学图像分割的新框架。为了演示这种方法,我们设计并开发了一个专用的开源软件工具,用于多模态图像分析MIASYS。该软件工具旨在通过集成自动算法、手动轮廓方法、图像预处理滤波器、后处理程序、用户交互功能和评估指标,为3D图像分割提供所需的解决方案。所提出的方法和附带的软件工具已经成功地评估了不同的放射治疗和放射诊断应用。
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Techniques and software tool for 3D multimodality medical image segmentation
The era of noninvasive diagnostic radiology and image-guided radiotherapy has witnessed burgeoning interest in applying different imaging modalities to stage and localize complex diseases such as atherosclerosis or cancer. It has been observed that using complementary information from multimodality images often significantly improves the robustness and accuracy of target volume definitions in radiotherapy treatment of cancer. In this work, we present techniques and an interactive software tool to support this new framework for 3D multimodality medical image segmentation. To demonstrate this methodology, we have designed and developed a dedicated open source software tool for multimodality image analysis MIASYS. The software tool aims to provide a needed solution for 3D image segmentation by integrating automatic algorithms, manual contouring methods, image preprocessing filters, post-processing procedures, user interactive features and evaluation metrics. The presented methods and the accompanying software tool have been successfully evaluated for different radiation therapy and diagnostic radiology applications.
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