论文标题
部分可观测时空混沌系统的无模型预测
Reference Based Color Transfer for Medical Volume Rendering
论文作者
论文摘要
医学成像的好处是巨大的。医学图像提供了大量的解剖信息,这有助于医生进行有效的疾病诊断并决定最佳的医疗过程。从传统的单色医学图像(例如CT扫描,X射线或MRI图像)转变为解剖结构的彩色3D表示,进一步增强了医疗专业人员在提取有价值的医疗信息方面的能力。我们的研究中提出的框架首先要通过在两个医学图像之间找到深层语义对应性进行色彩转移:彩色参考图像和单色CT扫描或MRI图像。我们扩展了基于参考的着色技术的想法,以从一堆灰度医学图像中执行彩色音量渲染。此外,我们还建议使用有效的参考图像建议系统来帮助选择良好的参考图像。通过我们的方法,我们成功地执行了彩色医疗量可视化,并基本上消除了用户交互的艰苦过程,以获得颜色和不透明度参数以进行音量渲染。
The benefits of medical imaging are enormous. Medical images provide considerable amounts of anatomical information and this facilitates medical practitioners in performing effective disease diagnosis and deciding upon the best course of medical treatment. A transition from traditional monochromatic medical images like CT scans, X-Rays or MRI images to a colored 3D representation of the anatomical structure further enhances the capabilities of medical professionals in extracting valuable medical information. The proposed framework in our research starts with performing color transfer by finding deep semantic correspondence between two medical images: a colored reference image, and a monochromatic CT scan or an MRI image. We extend this idea of reference-based colorization technique to perform colored volume rendering from a stack of grayscale medical images. Furthermore, we also propose to use an effective reference image recommendation system to aid in the selection of good reference images. With our approach, we successfully perform colored medical volume visualization and essentially eliminate the painstaking process of user interaction with a transfer function to obtain color and opacity parameters for volume rendering.