为手部解剖结构量身定制渲染函数，提升MRI图像清晰度。

We study the design of transfer functions for volumetric rendering of magnetic resonance imaging (MRI) datasets of human hands. Human hands are anatomically complex, containing various organs within a limited space, which presents challenges for volumetric rendering. We focus on hand musculoskeletal organs because they are volumetrically the largest inside the hand, and most important for the hand's main function, namely manipulation of objects. While volumetric rendering is a mature field, the choice of the transfer function for the different organs is arguably just as important as the choice of the specific volume rendering algorithm; we demonstrate that it significantly influences the clarity and interpretability of the resulting images. We assume that the hand MRI scans have already been segmented into the different organs (bones, muscles, tendons, ligaments, subcutaneous fat, etc.). Our method uses the hand MRI volume data, and the geometry of its inner organs and their known segmentation, to produce high-quality volume rendering images of the hand, and permits fine control over the appearance of each tissue. We contribute two families of transfer functions to emphasize different hand tissues of interest, while preserving the visual context of the hand. We also discuss and reduce artifacts present in standard volume ray-casting of human hands. We evaluate our volumetric rendering on five challenging hand motion sequences. Our experimental results demonstrate that our method improves hand anatomy visualization, compared to standard surface and volume rendering techniques.