Generation of variable anatomical models for surgical training simulators.

@article{citeulike:1325534, abstract = {The generation of variable surgical scenes is a key element for effective training with surgery simulators. Our current research aims at a high fidelity hysteroscopy simulator which challenges the trainee with a new surgical scene in every training session. We previously reported on methods able to generate a broad range of pathologies within an existing healthy organ model. This paper presents the methods necessary to produce variable models of the healthy organ. In order to build a database of uteri, a volunteer study was conducted. The segmentation was carried out interactively, also covering the establishment of an anatomically meaningful correspondence between the individual organs. The variability of the shape parameters has been characterized by principal component analysis. A new method has been developed and tested, allowing the derivation of realistic new instances based on the stochastic model and complying with non-linear shape constraints which are defined and interactively controlled by medical experts.}, address = {Department of Information Technology and Electrical Engineering, Computer Vision Laboratory, Sternwartstrasse 7, 8092 Zurich, ETH Z\"{u}rich, Switzerland. rsierra@ee.ethz.ch}, author = {Sierra, R. and Zsemlye, G. and Sz\'{e}kely, G. and Bajka, M. }, citeulike-article-id = {1325534}, doi = {http://dx.doi.org/10.1016/j.media.2005.11.003}, issn = {1361-8415}, journal = {Med Image Anal}, keywords = {anatomical, clinical, generation, model, parameters, shape, statistical}, month = {April}, number = {2}, pages = {275--285}, posted-at = {2007-05-24 18:40:12}, priority = {0}, title = {Generation of variable anatomical models for surgical training simulators.}, url = {http://dx.doi.org/10.1016/j.media.2005.11.003}, volume = {10}, year = {2006} }

TY - JOUR ID - citeulike:1325534 L3 - citeulike-article-id:1325534 TI - Generation of variable anatomical models for surgical training simulators. JF - Med Image Anal VL - 10 IS - 2 SP - 275 EP - 285 AD - Department of Information Technology and Electrical Engineering, Computer Vision Laboratory, Sternwartstrasse 7, 8092 Zurich, ETH Zürich, Switzerland. rsierra@ee.ethz.ch SN - 1361-8415 N2 - The generation of variable surgical scenes is a key element for effective training with surgery simulators. Our current research aims at a high fidelity hysteroscopy simulator which challenges the trainee with a new surgical scene in every training session. We previously reported on methods able to generate a broad range of pathologies within an existing healthy organ model. This paper presents the methods necessary to produce variable models of the healthy organ. In order to build a database of uteri, a volunteer study was conducted. The segmentation was carried out interactively, also covering the establishment of an anatomically meaningful correspondence between the individual organs. The variability of the shape parameters has been characterized by principal component analysis. A new method has been developed and tested, allowing the derivation of realistic new instances based on the stochastic model and complying with non-linear shape constraints which are defined and interactively controlled by medical experts. KW - anatomical KW - clinical KW - generation KW - model KW - parameters KW - shape KW - statistical AU - Sierra, R AU - Zsemlye, G AU - Székely, G AU - Bajka, M PY - 2006/04// UR - http://dx.doi.org/10.1016/j.media.2005.11.003 ER -