Tumor growth models to generate pathologies for surgical training simulators

Medical Image Analysis
R SierraG Székely

Abstract

Many virtual reality based surgical training simulators have been presented in the last few years. These systems promise to alleviate the lack of realistic training possibilities common to minimally invasive procedures. Virtual reality allows for riskless training on a wide range of findings in a condensed period of time. We investigated different methods for the generation of tumor models suitable for surgical training simulators. The goal of our research is a high fidelity hysteroscopy simulator which provides an individual surgical scene for every training. Emphasis was placed on the modeling of growth processes leading to the generation of macroscopically realistic findings of the most common pathologies in hysteroscopy, namely polyps and myomas found in the uterine cavity. Both a cellular automaton and a particle based tumor growth model are presented and discussed.

References

Jan 1, 1976·Journal of Theoretical Biology·H P Greenspan
Mar 7, 1993·Journal of Theoretical Biology·A S QiB S An
Sep 30, 1999·IEEE Transactions on Medical Imaging·S K KyriacouR N Bryan
Mar 29, 2000·Journal of Theoretical Biology·A R KansalT S Deisboeck
Apr 11, 2002·Nature Cell Biology·Colin Jamora, Elaine Fuchs
May 3, 2003·Journal of Mathematical Biology·Vittorio CristiniQing Nie
Nov 11, 2003·Journal of the Neurological Sciences·Kristin R SwansonEllsworth C Alvord
Mar 26, 2004·Clinical Anatomy : Official Journal of the American Association of Clinical Anatomists & the British Association of Clinical Anatomists·M BajkaP Groscurth
Jan 4, 2006·Medical Image Analysis·R SierraM Bajka

❮ Previous
Next ❯

Citations

Apr 26, 2008·Surgical Endoscopy·Michael BajkaMatthias Harders
Oct 23, 2012·BMC Medical Education·Trung Q TranPamela E Wright

❮ Previous
Next ❯

Related Concepts

Related Feeds

Cancer Imaging

Imaging techniques, including CT and MR, have become essential to tumor detection, diagnosis, and monitoring. Here is the latest research on cancer imaging.