论文标题
来自2D样式的多模式医学量着色
Multimodal Medical Volume Colorization from 2D Style
论文作者
论文摘要
着色涉及目标图像上颜色的合成，同时保留结构内容以及目标图像的语义。这是许多最先进的解决方案的2D问题。我们提出了一种基于3D医学量的化着色的新型深度学习方法。我们的系统能够实时将2D照片的颜色直接映射到3D MRI量，从而产生适合于逼真的可视化的高保真颜色量。由于这项工作首先是此类工作，因此我们详细讨论了完整的管道以及3D医疗数据带来的挑战。医学MRI量的着色还需要模态转换，这突出了我们处理多模式数据的鲁棒性。
Colorization involves the synthesis of colors on a target image while preserving structural content as well as the semantics of the target image. This is a well-explored problem in 2D with many state-of-the-art solutions. We propose a novel deep learning-based approach for the colorization of 3D medical volumes. Our system is capable of directly mapping the colors of a 2D photograph to a 3D MRI volume in real-time, producing a high-fidelity color volume suitable for photo-realistic visualization. Since this work is first of its kind, we discuss the full pipeline in detail and the challenges that it brings for 3D medical data. The colorization of medical MRI volume also entails modality conversion that highlights the robustness of our approach in handling multi-modal data.
