4D Dynamic Volume Rendering using Raycasting

A V Krishna Rao Padyala, Srinivasa Rao Namburi

Abstract


Medical imaging has become one of the most used diagnostic tools in the medical profession in the last three decades. Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) technologies have become widely adopted because of their ability to capture the human body in a non-invasive manner. A volumetric dataset is a series of orthogonal 2D slices captured at a regular interval, typically along the axis of the body from the head to the feet. Volume rendering is a computer graphics technique that allows volumetric data to be visualized and manipulated as a single 3D object. Some of the volume rendering methods are Isosurface rendering, image splatting , shear warp, texture slicing, and raycasting.

      CT and MRI hardware was limited to providing a single 3D scan of the human body. Functional imaging let capture of anatomical data over time.One of them is Functional MRI (fMRI), is used to capture changes in the human body over time.This paper presents creation of generic software capable of performing real-time 4D volume rendering via raycasting, on desktop.

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References


D.J. Goodenough, K.E. Weaver, Overview of Computed Tomography, IEEE Trans. Nucl.Sci. 26 (1979) 1661–1667. doi:10.1109/TNS.1979.4330458.

P.A. Bottomley, Nuclear magnetic resonance: Beyond physical imaging: A powerful new diagnostic tool that uses magnetic fields and radio waves creates pictures of the body’s internal chemistry, IEEE Spectr. 20 (1983) 32–38. doi:10.1109/MSPEC.1983.6369002.

K.K. Shung, M.B. Smith, B. Tsui, Principles of Medical Imaging, Academic Press, Inc.,San Diego, CA, 1992.

S. Roettger, S. Guthe, D. Weiskopf, T. Ertl, W. Strasser, Smart Hardware-Accelerated Volume Rendering, in: IEEE TCVG Symp. Vis., 2003: pp. 231–238.

W.M. Hsu, Segmented ray casting for data parallel volume rendering, in: Proc. 1993 IEEE Parallel Render. Symp., 1993: pp. 7–14. doi:10.1109/PRS.1993.586079.

K. Ma,Parallel volume raycasting for unstructured grid data on distributed memory architectures,in:IEEE Symp . Parallel Render.1995,1995:pp.23–30.doi:10.1145/218327. 218333.

K.-L.M.K.-L. Ma, T.W. Crockett, A scalable parallel cell-projection volume rendering algorithm for three-dimensional unstructured data, in: Proc. IEEE Symp. Parallel Render.,1997: pp. 95–104. doi:10.1109/PRS.1997.628300.

F. Di Salle, E. Formisano, D.E. Linden, R. Goebel, S. Bonavita, a Pepino, et al., Exploring brain function with magnetic resonance imaging., Eur. J. Radiol. 30 (1999) 84–94.http://www.ncbi.nlm.nih.gov/pubmed/10401589.

P.T. Fox, M.E. Raichle, Focal physiological uncoupling of cerebral blood flow and oxidative metabolism during somatosensory stimulation in human subjects., Proc. Natl.Acad. Sci. U. S. A. 83 (1986) 1140–1144. doi:10.1073/pnas.83.4.1140.

A. Hennemuth, O. Friman, C. Schumann, J. Bock, J. Drexl, M. Huellebrand, et al., Fast Interactive Exploration of 4D MRI Flow Data, 7964 (2011) 79640E–79640E–11.doi:10.1117 /12.878202.

C.J. Noon, A Volume Rendering Engine for Desktops, Laptops, Mobile Devices and Immersive Virtual Reality Systems using GPU-Based Volume Raycasting by, Iowa State University, 2012.




DOI: https://doi.org/10.23956/ijarcsse.v8i10.882

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