TY  - CONF
ID  - upm26117
TI  - Neuroanatomic-based detection algorithm for automatic labeling of brain structures in brain injury
T2  - XIII Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON 2013)
VL  - 41
UR  - https://oa.upm.es/26117/
SP  - 1694
EP  - 1697
AV  - public
Y1  - 2014///
KW  - Neuroimaging
KW  -  Descriptors
KW  -  Landmarks
KW  -  Magnetic Resonance Imaging (MRI)
KW  -  Neuroanatomic Structures
A1  - Luna Serrano, Marta
A1  - Gayá Moreno, Francisco Javier
A1  - García Molina, A.
A1  - González Rivas, Luis Miguel
A1  - Cáceres Taladriz, César
A1  - Bernabeu Guitart, M.
A1  - Roig Rovira, Teresa
A1  - Pascual Leone, Álvaro
A1  - Tormos Muñoz, Josep M.
A1  - Gómez Aguilera, Enrique J.
M2  - Sevilla, Spain
PB  - Springer
N2  - 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.
ER  -