| dc.creator | Namías, Rafael | |
| dc.creator | Fresno, Mariana del | |
| dc.creator | D’Amato, J. P. | |
| dc.creator | Bellemare, M. E. | |
| dc.creator | Vénere, Marcelo | |
| dc.date | 2012-08 | |
| dc.date | 2012 | |
| dc.date | 2021-08-31T12:31:49Z | |
| dc.date.accessioned | 2023-07-15T03:01:32Z | |
| dc.date.available | 2023-07-15T03:01:32Z | |
| dc.identifier | http://sedici.unlp.edu.ar/handle/10915/123790 | |
| dc.identifier | https://41jaiio.sadio.org.ar/sites/default/files/4_AST_2012.pdf | |
| dc.identifier | issn:1850-2806 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/7464161 | |
| dc.description | In this work we present part of a Pelvis Dynamics Modeling System for pre-surgical assistance in the pelvic organ prolapse disease. In this condition, the most common affected organs are the uterus, the bladder and the rectum. The Magnetic Resonance Imaging (MRI) is the gold standard non-invasive imaging technique to evaluate this condition. The MRI’s acquisitions provide spatial information that is essential to build tri-dimensional (3D) models and run physical simulations that recreate the prolapse. In these acquisitions, the above mentioned organs, present blurred borders and different textures. Therefore, its extraction in not trivial at all. We pose an hybrid semi-automatic segmentation strategy which combines Region Growing (RG) and Active Surfaces in MRI scans to retrieve surface meshes of the organs of interest. We show some real cases, one applying the complete process in detail and the others, providing final results attained by the method which shows high quality segmentations achieved with a low computational cost. | |
| dc.description | Sociedad Argentina de Informática e Investigación Operativa | |
| dc.format | application/pdf | |
| dc.format | 37-48 | |
| dc.language | en | |
| dc.rights | http://creativecommons.org/licenses/by-nc-sa/4.0/ | |
| dc.rights | Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) | |
| dc.subject | Ciencias Informáticas | |
| dc.subject | Medical Imaging | |
| dc.subject | Segmentation | |
| dc.subject | Active Surfaces | |
| dc.subject | Magnetic Resonance | |
| dc.title | Volumetric Segmentation of Pelvic Organs from MRI Acquisitions | |
| dc.type | Objeto de conferencia | |
| dc.type | Objeto de conferencia | |
