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.
翻译:医学图象提供了大量的解剖学信息,有助于医疗从业人员进行有效的疾病诊断和决定最佳治疗过程。从传统的单色医学图象,如CT扫描、X射线或MRI图象,过渡到有色3D的解剖结构图象,进一步提高了医学专业人员提取宝贵医疗信息的能力。我们研究中的拟议框架首先通过在两种医学图象(彩色参考图象和单色CT扫描或MRI图象)之间找到深层次的语义通信进行色传输。我们把这种基于参考的彩色化技术的理念推广到从一堆灰度医学图象中进行彩色量转换。此外,我们还提议使用有效的参考图象建议系统,帮助选择良好的参考图象。我们的方法是,我们成功地进行有色医学量的可视化,并基本上消除用户与传输功能之间的艰难互动过程,以获得量制作的颜色和不透明性参数。