Top recommendation: Efficiently displaying voxel-based data using WebGL

I am in search of the most effective practice or practices for solving the following problem. I will strive to describe it in a way that is abstract enough to be applied to unforeseen scenarios.

Available data consists of Voxels (volumetric pixels) forming a cube with coordinates x, y, z and an attached color.

The objective is to utilize OpenGL to display this data as you navigate through it from various perspectives.

The question at hand is: What is the optimal approach to rendering these voxels based on the viewpoint? How should the data be stored?

Considerations to keep in mind:

  • The cube of data can be viewed as z layers of x y data. It should allow for viewing between layers, with the displayed color being interpolated from the nearest matching voxels.
  • For my specific application, I have datasets with dimensions of (x, y, z) = (512, 512, 128) and beyond, containing medical data such as scans of hearts and brains.

What I have attempted thus far includes evaluating different frameworks (such as PIXI.js and three.js) and going through several WebGL tutorials.

If anything remains unclear, please do not hesitate to inquire further.

javascriptopengl-esthree.jswebglpixi.js

Answer №1

When it comes to representing 3D datasets, there are two main techniques: rasterization and ray-tracing. A common approach in rasterization is using algorithms like Marching Cubes, Dual Contouring, or Dual Marching Cubes for surface reconstruction.

For example, Three.js offers a Marching Cubes implementation in its examples section. This method involves creating polygons from voxels for rasterization, which can be surprisingly fast depending on the level of detail required. However, if you want to represent more than just cubes, you'll need additional information beyond just voxel positions and colors.

On the other hand, raycasting is another technique but requires an efficient algorithm to avoid performance issues. By casting rays from the camera position through the data structure, locating the surface, and projecting the intersection points back onto the screen with the correct color, you can create detailed images. These pixels can then be mapped onto a full-screen quad using a shader.

In both approaches, having additional data such as density values or intersection normals is crucial for accurate representation. Organizing the data efficiently, especially for out-of-core accesses, is also key to optimizing performance.

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