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Advancements in Computer-Assisted Minimal Invasive Surgery through Guided Motor Control

This paper explores the evolution of minimal invasive surgery, highlighting its advantages over traditional methods, such as reduced postoperative complications and minimal scarring. It addresses challenges like restricted visibility and the difficulty in acquiring necessary motor skills. The proposed solutions involve utilizing advanced sensors, three-dimensional camera systems, and computer tomography to enhance depth perception and visibility. Computer simulations serve as training tools, allowing surgeons to practice and refine their techniques without the need for actual surgical procedures.

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Advancements in Computer-Assisted Minimal Invasive Surgery through Guided Motor Control

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  1. Computer Assisted Minimal Invasive Surgery towards Guided Motor Control By: Vinay B Gavirangaswamy

  2. Introduction • 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. Solution Approach • 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. Computer Tomography “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. Key Terminologies • 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. Key Terminologies (Contd.) • Phantom- construction of a planar figure from view points

  7. Set of Projections Filtered Back Projections • 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

  8. Algebraic Reconstruction Methods • 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. Algebraic Reconstruction Method Disadvantage (iterative method) Advantages overfiltered back propagation • 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* * Similar to Parallel Implementations of Gaussian elimination Vasilije’s Project

  10. Refences • J.C. Russ, The image processing Handbook CRC Press (1992) • Raman Rao, Ronald D. Krizet 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

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