Detailed anatomical information is essential to optimize medical decisions for surgical and pre-operative planning in patients with congenital heart disease. The visualization techniques commonly used in clinical routine for the exploration of complex cardiac data are based on multi-planar reformations, maximum intensity projection, and volume rendering, which rely on basic lighting models prone to image distortion. On the other hand, cinematic rendering (CR), a three-dimensional visualization technique based on physically-based rendering methods, can create volumetric images with high fidelity. However, there are a lot of parameters involved in CR that affect the visualization results, thus being dependent on the user's experience and requiring detailed evaluation protocols to compare available solutions. In this study, we have analyzed the impact of the most relevant parameters in a CR pipeline developed in the open-source version of the MeVisLab framework for the visualization of the heart anatomy of three congenital patients and two adults from CT images. The resulting visualizations were compared to a commercial tool used in the clinics with a questionnaire filled in by clinical users, providing similar definitions of structures, depth perception, texture appearance, realism, and diagnostic ability.

翻译：精准的解剖学信息对优化先天性心脏病患者手术和术前规划的医疗决策至关重要。临床常规用于复杂心脏数据探查的可视化技术基于多平面重建、最大强度投影及依赖易致图像失真的基本光照模型的体绘制。另一方面，基于物理渲染方法的三维可视化技术——电影级渲染（CR），能够生成高保真度的容积图像。然而，CR涉及大量影响可视化结果的参数，因此其效果依赖于用户经验，并需要详细的评估方案来比较现有解决方案。本研究分析了基于CT图像的三位先天性患者及两位成年患者心脏解剖可视化过程中，开源版MeVisLab框架所开发的CR流程中最相关参数的影响。通过临床用户填写的问卷，将生成的可视化结果与临床使用的商业工具进行对比，在结构定义相似性、深度感知、纹理表现、真实感和诊断能力方面进行了评估。