Modern gaming GPUs were originally developed to accelerate the complex mathematical calculations required for CT scans.

The evolution of the Graphics Processing Unit (GPU) is deeply rooted in the need for high-speed parallel processing. In the 1970s and 1980s, Computed Tomography (CT) scans required massive computational power to reconstruct 2D X-ray data into 3D models. This process, known as filtered back-projection, involves solving millions of linear equations at once.General-purpose CPUs were too slow for this task because they process data sequentially. To solve this, researchers developed specialized hardware accelerators capable of performing many calculations in parallel. This breakthrough allowed doctors to view internal organs in high detail without waiting hours for a computer to finish processing the data.By the late 1990s, companies like NVIDIA and ATI realized that the math used for medical reconstruction was nearly identical to the math needed for 3D graphics. Both fields rely on matrix transformations and floating-point arithmetic to determine where pixels or voxels should appear on a screen. The NVIDIA GeForce 256, released in 1999, is often cited as the world's first true GPU, bringing this industrial-grade power to home consumers.Today, the relationship has come full circle. Modern GPUs are used not only for gaming but also for advanced AI research, climate modeling, and real-time robotic surgery. The parallel processing architecture that started with medical imaging now powers everything from ray-traced shadows in games to the deep learning models used by ChatGPT.