Automated Multi-Contrast Brain Pathological Area Extraction from 2D MR Images



Título del documento: Automated Multi-Contrast Brain Pathological Area Extraction from 2D MR Images
Revista: Journal of applied research and technology
Base de datos: PERIÓDICA
Número de sistema: 000384565
ISSN: 1665-6423
Autores: 1
1
2
1
Instituciones: 1Academy of Sciences of the Czech Republic, Institute of Scientific Instruments, Brno, Jihomoravsky. República Checa
2Vienna University of Technology, Faculty of Informatics, Viena. Austria
Año:
Periodo: Feb
Volumen: 13
Número: 1
Paginación: 58-69
País: México
Idioma: Inglés
Tipo de documento: Artículo
Enfoque: Aplicado, descriptivo
Resumen en inglés The aim of this work is to propose the fully automated pathological area extraction from multi-parametric 2D MR images of brain. The proposed method is based on multi-resolution symmetry analysis and automatic thresholding. The proposed algorithm first detects the presence of pathology and then starts its extraction. T2 images are used for the presence detection and the multi-contrast MRI is used for the extraction, concretely T2 and FLAIR images. The extraction is based on thresholding, where Otsu's algorithm is used for the automatic determination of the threshold. Since the method is based on symmetry, it works for both axial and coronal planes. In both these planes of healthy brain, the approximate left-right symmetry exists and it is used as the prior knowledge for searching the approximate pathology location. It is assumed that this area is not located symmetrically in both hemispheres, which is met in most cases. The detection algorithm was tested on 203 T2-weighted images and reached the true positive rate of 87.52% and true negative rate of 93.14%. The extraction algorithm was tested on 357 axial and 443 coronal real images from publicly available BRATS databases containing 3D volumes brain tumor patients. The results were evaluated by Dice Coefficient (axial: 0.85±0.11, coronal 0.82±0.18) and by Accuracy (axial: 0.96±0.05, coronal 0.94±0.09)
Disciplinas: Ingeniería,
Medicina
Palabras clave: Diagnóstico,
Neurología,
Oncología,
Ingeniería biomédica,
Tumor cerebral,
Resonancia magnética,
Análisis de simetría
Keyword: Engineering,
Medicine,
Diagnosis,
Neurology,
Oncology,
Biomedical engineering,
Brain tumor,
Magnetic resonance,
Symmetry analysis
Texto completo: Texto completo (Ver HTML)