Automatic segmentation of abdominal aortic aneurysm from medical images based on active shape models and texture models

Tarjuelo Gutierrez, Jaime, Rodríguez Vila, Borja and Gómez Aguilera, Enrique J. 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. In: "II Joint Workshop on New Technologies for Computer/Robot Assisted Surgery", 09/07/2012 - 10/07/2012, Madrid, Spain. pp. 5-9.

Description

Title: Automatic segmentation of abdominal aortic aneurysm from medical images based on active shape models and texture models
Author/s:
Item Type: Presentation at Congress or Conference (Article)
Event Title: II Joint Workshop on New Technologies for Computer/Robot Assisted Surgery
Event Dates: 09/07/2012 - 10/07/2012
Event Location: Madrid, Spain
Title of Book: II Joint Workshop on New Technologies for Computer/Robot Assisted Surgery
Date: 2012
Subjects:
Freetext Keywords: Segmentation, abdominal aortic aneurysm, intraluminal thrombus, active appearance models
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Tecnología Fotónica [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

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.

More information

Item ID: 22730
DC Identifier: https://oa.upm.es/22730/
OAI Identifier: oai:oa.upm.es:22730
Deposited by: Memoria Investigacion
Deposited on: 05 Mar 2014 16:44
Last Modified: 21 Apr 2016 19:41
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