Neuroanatomic-based detection algorithm for automatic labeling of brain structures in brain injury

Luna Serrano, Marta and Gayá Moreno, Francisco Javier and García Molina, A. and González Rivas, Luis Miguel and Cáceres Taladriz, César and Bernabeu Guitart, M. and Roig Rovira, Teresa and Pascual Leone, Álvaro and Tormos Muñoz, Josep M. and Gómez Aguilera, Enrique J. (2014). Neuroanatomic-based detection algorithm for automatic labeling of brain structures in brain injury. In: "XIII Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON 2013)", 25/09/2013 - 28/09/2013, Sevilla, Spain. pp. 1694-1697. https://doi.org/10.1007/978-3-319-00846-2_418.

Description

Title: Neuroanatomic-based detection algorithm for automatic labeling of brain structures in brain injury
Author/s:
  • Luna Serrano, Marta
  • Gayá Moreno, Francisco Javier
  • García Molina, A.
  • González Rivas, Luis Miguel
  • Cáceres Taladriz, César
  • Bernabeu Guitart, M.
  • Roig Rovira, Teresa
  • Pascual Leone, Álvaro
  • Tormos Muñoz, Josep M.
  • Gómez Aguilera, Enrique J.
Item Type: Presentation at Congress or Conference (Article)
Event Title: XIII Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON 2013)
Event Dates: 25/09/2013 - 28/09/2013
Event Location: Sevilla, Spain
Title of Book: IFMBE Proceedings
Date: 2014
Volume: 41
Subjects:
Freetext Keywords: Neuroimaging, Descriptors, Landmarks, Magnetic Resonance Imaging (MRI), Neuroanatomic Structures
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

The number and grade of injured neuroanatomic structures and the type of injury determine the degree of impairment after a brain injury event and the recovery options of the patient. However, the body of knowledge and clinical intervention guides are basically focused on functional disorder and they still do not take into account the location of injuries. The prognostic value of location information is not known in detail either. This paper proposes a feature-based detection algorithm, named Neuroanatomic-Based Detection Algorithm (NBDA), based on SURF (Speeded Up Robust Feature) to label anatomical brain structures on cortical and sub-cortical areas. Themain goal is to register injured neuroanatomic structures to generate a database containing patient?s structural impairment profile. This kind of information permits to establish a relation with functional disorders and the prognostic evolution during neurorehabilitation procedures.

More information

Item ID: 26117
DC Identifier: http://oa.upm.es/26117/
OAI Identifier: oai:oa.upm.es:26117
DOI: 10.1007/978-3-319-00846-2_418
Deposited by: Memoria Investigacion
Deposited on: 27 May 2014 18:37
Last Modified: 01 Feb 2015 23:56
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