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Automatic segmentation of abdominal aortic aneurysm from medical images based on active shape models and texture models
Cita
Tarjuelo Gutiérrez, Jaime, Rodríguez Vila, Borja and Gómez Aguilera, Enrique Javier 
ORCID: https://orcid.org/0000-0001-6998-1407
(2012).
Automatic segmentation of abdominal aortic aneurysm from medical images based on active shape models and texture models.
En: "II Joint Workshop on New Technologies for Computer/Robot Assisted Surgery", 09/07/2012 - 10/07/2012, Madrid, Spain. pp. 5-9.
ORCID: https://orcid.org/0000-0001-6998-1407
(2012).
Automatic segmentation of abdominal aortic aneurysm from medical images based on active shape models and texture models.
En: "II Joint Workshop on New Technologies for Computer/Robot Assisted Surgery", 09/07/2012 - 10/07/2012, Madrid, Spain. pp. 5-9.
Descripción
| Título: | Automatic segmentation of abdominal aortic aneurysm from medical images based on active shape models and texture models |
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| Autor/es: |
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| Tipo de Documento: | Ponencia en Congreso o Jornada (Artículo) |
| Título del Evento: | II Joint Workshop on New Technologies for Computer/Robot Assisted Surgery |
| Fechas del Evento: | 09/07/2012 - 10/07/2012 |
| Lugar del Evento: | Madrid, Spain |
| Título del Libro: | II Joint Workshop on New Technologies for Computer/Robot Assisted Surgery |
| Fecha: | 2012 |
| Materias: | |
| ODS: | |
| Palabras Clave Informales: | Segmentation, abdominal aortic aneurysm, intraluminal thrombus, active appearance models |
| Escuela: | E.T.S.I. Telecomunicación (UPM) |
| Departamento: | Tecnología Fotónica [hasta 2014] |
| Licencias Creative Commons: | Reconocimiento - Sin obra derivada - No comercial |
Resumen
A semi-automatic segmentation algorithm for abdominal aortic aneurysms (AAA), and based on Active Shape Models (ASM) and texture models, is presented in this work. The texture information is provided by a set of four 3D magnetic resonance (MR) images, composed of axial slices of the abdomen, where lumen, wall and intraluminal thrombus (ILT) are visible. Due to the reduced number of images in the MRI training set, an ASM and a custom texture model based on border intensity statistics are constructed. For the same reason the shape is characterized from 35-computed tomography angiography (CTA) images set so the shape variations are better represented. For the evaluation, leave-one-out experiments have been held over the four MRI set.
Más información
| ID de Registro: | 22730 |
|---|---|
| Identificador DC: | https://oa.upm.es/22730/ |
| Identificador OAI: | oai:oa.upm.es:22730 |
| Depositado por: | Memoria Investigacion |
| Depositado el: | 05 Mar 2014 16:44 |
| Ultima Modificación: | 06 Jun 2024 11:24 |
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