  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.
