Journal of Real-Time Image Processing

, Volume 1, Issue 4, pp 285–301 | Cite as

FPGA-based real-time 3D image preprocessing for image-guided medical interventions

  • Omkar Dandekar
  • Carlos Castro-Pareja
  • Raj Shekhar
Priginal Research Paper

Abstract

Minimally invasive image-guided interventions (IGIs) are time and cost efficient, minimize unintended damage to healthy tissue, and lead to faster patient recovery. One emerging trend in IGI workflow is to use volumetric imaging modalities such as low-dose computed tomography (CT) and 3D ultrasound to provide real-time, accurate anatomical information intraoperatively. These intraoperative images, however, are often characterized by quantum (in low-dose CT) or speckle (in ultrasound) noise and must be enhanced prior to any advanced image processing. Anisotropic diffusion filtering and median filtering have been shown to be effective in enhancing and improving the visual quality of these images. However, achieving real-time performance, as required by IGIs, using software-only implementations is challenging because of the sheer size of the images and the arithmetic complexity of the filtering operations. We present a field-programmable gate array-based reconfigurable architecture for real-time preprocessing of intraoperative 3D images. The proposed architecture provides programmable kernels for 3D anisotropic diffusion filtering and 3D median filtering within the same framework. The implementation of this architecture using an Altera Stratix-II device achieved a voxel processing rate close to 200 MHz, which enables the use of these processing techniques in the IGI workflow prior to advanced operations such as segmentation, registration, and visualization.

Keywords

Image-guided interventions 3D anisotropic diffusion 3D median filtering Real-time image processing Field-programmable gate array 

Notes

Acknowledgments

This work was partially supported by the Department of Defense grant DAMD17-03-2-0001. The authors would like to thank Dr. Vivek Walimbe and Dr. Nancy Knight for their help in editing and refining this manuscript. The authors also thank the anonymous reviewers for their feedback and suggestions in improving this manuscript.

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Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Omkar Dandekar
    • 1
    • 2
  • Carlos Castro-Pareja
    • 2
  • Raj Shekhar
    • 1
    • 2
  1. 1.Department of Electrical and Computer EngineeringUniversity of MarylandCollege ParkUSA
  2. 2.Department of Diagnostic Radiology and Nuclear Medicine, N2W78University of MarylandBaltimoreUSA

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