Segmentation of corpus callosum using diffusion tensor imaging: validation in patients with glioblastoma.
BMC Med Imaging
; 12: 10, 2012 May 16.
Article
en En
| MEDLINE
| ID: mdl-22591335
ABSTRACT
BACKGROUND:
This paper presents a three-dimensional (3D) method for segmenting corpus callosum in normal subjects and brain cancer patients with glioblastoma.METHODS:
Nineteen patients with histologically confirmed treatment naïve glioblastoma and eleven normal control subjects underwent DTI on a 3T scanner. Based on the information inherent in diffusion tensors, a similarity measure was proposed and used in the proposed algorithm. In this algorithm, diffusion pattern of corpus callosum was used as prior information. Subsequently, corpus callosum was automatically divided into Witelson subdivisions. We simulated the potential rotation of corpus callosum under tumor pressure and studied the reproducibility of the proposed segmentation method in such cases.RESULTS:
Dice coefficients, estimated to compare automatic and manual segmentation results for Witelson subdivisions, ranged from 94% to 98% for control subjects and from 81% to 95% for tumor patients, illustrating closeness of automatic and manual segmentations. Studying the effect of corpus callosum rotation by different Euler angles showed that although segmentation results were more sensitive to azimuth and elevation than skew, rotations caused by brain tumors do not have major effects on the segmentation results.CONCLUSIONS:
The proposed method and similarity measure segment corpus callosum by propagating a hyper-surface inside the structure (resulting in high sensitivity), without penetrating into neighboring fiber bundles (resulting in high specificity).
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Neoplasias Encefálicas
/
Reconocimiento de Normas Patrones Automatizadas
/
Interpretación de Imagen Asistida por Computador
/
Técnica de Sustracción
/
Glioblastoma
/
Cuerpo Calloso
/
Imagen de Difusión por Resonancia Magnética
Tipo de estudio:
Diagnostic_studies
/
Guideline
Límite:
Female
/
Humans
/
Male
/
Middle aged
Idioma:
En
Revista:
BMC Med Imaging
Asunto de la revista:
DIAGNOSTICO POR IMAGEM
Año:
2012
Tipo del documento:
Article
País de afiliación:
Irán