Int J Comput Assist Radiol Surg - Fast reconstructed radiographs from octree-compressed volumetric data.

Tópicos

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Resumo

RPOSE: Simulated 2D X-ray images called digitally reconstructed radiographs (DRRs) have important applications within medical image registration frameworks where they are compared with reference X-rays or used in implementations of digital tomosynthesis (DTS). However, rendering DRRs from a CT volume is computationally demanding and relatively slow using the conventional ray-casting algorithm. Image-guided radiation therapy systems using DTS to verify target location require a large number DRRs to be precomputed since there is insufficient time within the automatic image registration procedure to generate DRRs and search for an optimal pose.METHOD: DRRs were rendered from octree-compressed CT data. Previous work showed that octree-compressed volumes rendered by conventional ray casting deliver a registration with acceptable clinical accuracy, but efficiently rendering the irregular grid of an octree data structure is a challenge for conventional ray casting. We address this by using vertex and fragment shaders of modern graphics processing units (GPUs) to directly project internal spaces of the octree, represented by textured particle sprites, onto the view plane. The texture is procedurally generated and depends on the CT pose.RESULTS: The performance of this new algorithm was found to be 4 times faster than that of a ray-casting algorithm implemented using NVIDIA?Compute Unified Device Architecture (CUDA?) on an equivalent GPU (~95?% octree compression). Rendering artifacts are apparent (consistent with other splatting algorithm), but image quality tends to improve with compression and fewer particles are needed. A peak signal-to-noise ratio analysis confirmed that the images rendered from compressed volumes were of marginally better quality to those rendered using Gaussian footprints.CONCLUSIONS: Using octree-encoded DRRs within a 2D/3D registration framework indicated the approach may be useful in accelerating automatic image registration.

Resumo Limpo

rpose simul d xray imag call digit reconstruct radiograph drrs import applic within medic imag registr framework compar refer xray use implement digit tomosynthesi dts howev render drrs ct volum comput demand relat slow use convent raycast algorithm imageguid radiat therapi system use dts verifi target locat requir larg number drrs precomput sinc insuffici time within automat imag registr procedur generat drrs search optim posemethod drrs render octreecompress ct data previous work show octreecompress volum render convent ray cast deliv registr accept clinic accuraci effici render irregular grid octre data structur challeng convent ray cast address use vertex fragment shader modern graphic process unit gpus direct project intern space octre repres textur particl sprite onto view plane textur procedur generat depend ct poseresult perform new algorithm found time faster raycast algorithm implement use nvidiacomput unifi devic architectur cuda equival gpu octre compress render artifact appar consist splat algorithm imag qualiti tend improv compress fewer particl need peak signaltonois ratio analysi confirm imag render compress volum margin better qualiti render use gaussian footprintsconclus use octreeencod drrs within dd registr framework indic approach may use acceler automat imag registr

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