title: Fractal analysis of tumoral lesions in brain.
abstract: In this work, it is proposed a method for supervised characterization and classification of tumoral lesions in brain, based on the analysis of irregularities at the lesion contour on T2-weighted MR images. After the choice of a specific image, a segmentation procedure with a threshold selected from the histogram of intensity levels is applied to isolate the lesion, the contour is detected through the application of a gradient operator followed by a conversion to a "time series" using a chain code procedure. The correlation dimension is calculated and analyzed to discriminate between normal or malignant structures. The results found showed that it is possible to detect a differentiation between benign (cysts) and malignant (gliomas) lesions suggesting the potential of this method as a diagnostic tool.
authors.affiliation: Centro de Física Molecular y Médica, Escuela de Física, Facultad de Ciencias, Universidad Central de Venezuela, A.P. 47586, Caracas 1041-A, Venezuela. mmartin@fisica.ciens.ucv.ve
authors.forename: Miguel
authors.initials: M
authors.lastname: Martín-Landrove
authors.forename: Demian
authors.initials: D
authors.lastname: Pereira
authors.forename: María E
authors.initials: ME
authors.lastname: Caldeira
authors.forename: Salvador
authors.initials: S
authors.lastname: Itriago
authors.forename: María
authors.initials: M
authors.lastname: Juliac
mesh_terms: D000465:Algorithms; D001932:Brain Neoplasms / Q000473:pathology*; D005103:Expert Systems; D017709:Fractals; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity