1. C OMPUTER A SSISTED M INIMAL I NVASIVE S URGERY TOWARDS G UIDED M OTOR C ONTROL By: Vinay B Gavirangaswamy

2. I NTRODUCTION Minimal invasive surgery is practiced over conventional open surgical methods Advantageous over traditional techniques as it minimizes post operative complications and leave minimum scars on the body Restricted visibility and dept perception Difficult to acquire required new motor skills Difficult to gain experience to develop required motor skills Very few or no alternatives other than performing actual surgery as teaching method

3. S OLUTION A PPROACH Increased use of sensors to assist in depth perception Three-dimensional camera system Computer Tomography as substitute for improved visibility and depth perception Computer simulation to act a simulation tool using actual instruments

4. C OMPUTER T OMOGRAPHY “Any method that reconstructs internal structural information within an object by mathematically reconstructing it from a series of projections”. Construction techniques Set of projection Filtered back projection Algebraic reconstruction methods

5. K EY T ERMINOLOGIES Constructed using linear attenuation coefficient μ Depends on element composition and density Volume element (voxel) a value in three dimensional space, is analogous to pixel in 2D image. Intensity at voxel is calculated by - incident intensity - detected intensity Sinogram/Radon – View taken from axis position t and at an angle Φ

6. K EY T ERMINOLOGIES (C ONTD.) Phantom- construction of a planar figure from view points

7. Uses rectangular co- ordinate system Projections from all the views contribute too much to the center of the image, and causes overlap (blurring) Uses polar co-ordinate system Inverse transformation removes blurring Set of Projections Filtered Back Projections

8. A LGEBRAIC R ECONSTRUCTION M ETHODS Calculation of linear attenuation coefficient is considered as set of simultaneous equations; written in the form n – number of voxels m – number of projections A – is the matrix of weights x- voxel values b-projection measurements are the b values

9. A LGEBRAIC R ECONSTRUCTION M ETHOD No single point that represents stable answer Convergence may not be very fast When to stop? Requires small number of view points compared to FBP FBP view points need to be equally spaced Acceptable reconstruction is possible through under sampled projections Can be parallelized* Disadvantage (iterative method) Advantages over filtered back propagation * Similar to Parallel Implementations of Gaussian elimination Vasilije’s Project

10. R EFENCES J.C. Russ, The image processing Handbook CRC Press (1992) Raman Rao, Ronald D. Kriz et al, “Parallel Implementation of the Filtered Back Projection Algorithm for Tomographic Imaging”, Internet: http://www.sv.vt.edu/xray_ct/parallel/Parallel_ CT.html, February 8, 2012 http://www.sv.vt.edu/xray_ct/parallel/Parallel_ CT.html