Hardware Accelerated Multi-coordinate Viewing Framework for Volumetric Visualization of Large 3D Medical Dataset

Abstract

Abstract The advances in Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) scanning techniques are improving the resolution and size of the volume datasets. The prevalence of three dimensional volumetric data is rapidly expanding with the internal information in the different resolution sizes of the dataset. In this paper we proposed an approach that can visualize the inner organs structure of the visible human male dataset in Multi-coordinate Viewing (MCV) framework. This can help to medical experts that are able to peer inside anatomy of the human medical dataset. The volume rendering part has been carried out by the utilization of enhanced ray casting algorithm for the crossing points of 3D square strategy for voxels. We present this system using Graphics Processing Unit or GPU-accelerated Compute Unified Device Architecture (CUDA) based approach for the focusing a specific region while zooming operation. The final results would allow the doctors to diagnose and analyze the atlas of 8-bit CT-scan data using three dimensional visualization with the efficient frame rate rendering speed in multi-operations like zooming, rotating, dragging. The framework is tested for visible human male dataset prepared by National Library of Medicine (NLM, USA) of size 1.2 GB.