The sparse data extrapolation problem: Strategies for soft-tissue correction for image-guided liver surgery Conference Paper
| Authors: | Miga, M. I.; Dumpuri, P.; Simpson, A. L.; Weis, J. A.; Jarnagin, W. R. |
| Title: | The sparse data extrapolation problem: Strategies for soft-tissue correction for image-guided liver surgery |
| Conference Title: | Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling |
| Abstract: | The problem of extrapolating cost-effective relevant information from distinctly finite or sparse data, while balancing the competing goals between workflow and engineering design, and between application and accuracy is the 'sparse data extrapolation problem'. Within the context of open abdominal image-guided liver surgery, one realization of this problem is compensating for non-rigid organ deformations while maintaining workflow for the surgeon. More specifically, rigid organ-based surface registration between CT-rendered liver surfaces and laser-range scanned intraoperative partial surface counterparts resulted in an average closest-point residual 6.1 ± 4.5 mm with maximum-signed distances ranging from -13.4 to 16.2 mm. Similar to the neurosurgical environment, there is a need to correct for soft tissue deformation to translate image-guided interventions to the abdomen (e.g. liver, kidney, pancreas, etc.). While intraoperative tomographic imaging is available, these approaches are less than optimal solutions to the sparse data extrapolation problem. In this paper, we compare and contrast three sparse data extrapolation methods to that of datarich interpolation for the correction of deformation within a liver phantom containing 43 subsurface targets. The findings indicate that the subtleties in the initial alignment pose following rigid registration can affect correction up to 5-10%. The best deformation compensation achieved was approximately 54.5% (target registration error of 2.0 ± 1.6 mm) while the data-rich interpolative method was 77.8% (target registration error of 0.6 ± 0.5 mm). © 2011 SPIE. |
| Keywords: | soft tissue; liver; computerized tomography; medical imaging; liver surgery; laser surgery; visualization; tissue engineering; tissue; deformation; intra-operative; image-guided; data visualization; deformation correction; finite element; image-guided surgery; deformation compensation; deformation corrections; engineering design; image guided surgery; image-guided intervention; initial alignment; non-rigid; optimal solutions; organ deformation; partial surfaces; rigid registration; soft tissue deformation; sparse data; subsurface targets; surface registration; target registration errors; tomographic imaging; error compensation; extrapolation |
| Journal Title | Proceedings of SPIE |
| Volume: | 7964 |
| Conference Dates: | 2011 Feb 13 |
| Conference Location: | Lake Buena Vista, FL |
| ISBN: | 0277-786X |
| Publisher: | SPIE |
| Date Published: | 2011-01-01 |
| Start Page: | 79640C |
| Language: | English |
| DOI: | 10.1117/12.878696 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | --- - Progress in Biomedical Optics and Imaging - Proceedings of SPIE - Progr. Biomed. Opt. Imaging Proc. SPIE - "Conference code: 84755" - "Export Date: 23 June 2011" - "Art. No.: 79640C" - "Sponsors: The Society of Photo-Optical Instrumentation Engineers (SPIE); Dynasil Corporation/RMD Research; American Association of Physicists in Medicine (AAPM); DQE Instruments, Inc.; Ocean Thin Films, Inc." - 13 February 2011 through 15 February 2011 - "Source: Scopus" |
