The Utility of Cloud Computing in Analyzing GPU-Accelerated Deformable Image Registration of CT and CBCT Images in Head and Neck Cancer Radiation Therapy

IEEE Journal of Translational Engineering in Health and Medicine
George ZakiRaj Shekhar

Abstract

The images generated during radiation oncology treatments provide a valuable resource to conduct analysis for personalized therapy, outcomes prediction, and treatment margin optimization. Deformable image registration (DIR) is an essential tool in analyzing these images. We are enhancing and examining DIR with the contributions of this paper: 1) implementing and investigating a cloud and graphic processing unit (GPU) accelerated DIR solution and 2) assessing the accuracy and flexibility of that solution on planning computed tomography (CT) with cone-beam CT (CBCT). Registering planning CTs and CBCTs aids in monitoring tumors, tracking body changes, and assuring that the treatment is executed as planned. This provides significant information not only on the level of a single patient, but also for an oncology department. However, traditional methods for DIR are usually time-consuming, and manual intervention is sometimes required even for a single registration. In this paper, we present a cloud-based solution in order to increase the data analysis throughput, so that treatment tracking results may be delivered at the time of care. We assess our solution in terms of accuracy and flexibility compared with a commercial tool register...Continue Reading

Software Mentioned

GPU Unified Device Architecture ( CUDA
Velocity
Elastix
VS
GPU
CUDA
Insight Segmentation and Registration Toolkit ( ITK )
DIR
Velocity Medical
Velocity Advanced Imaging

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