Nosologic maps of brain tumor images obtained from combination of different MRI modalities.
Tissue classification is a necessary step to obtain the spatial distribution of a pathology or nosologic map and typically it is performed by the combination of different medical image modalities, including histopathological studies. In previous work, combination of different magnetic resonance (MR) modalities such as in vivo spectroscopy, relaxometry and diffusometry have been proposed to obtain nosologic maps with appropriate spatial resolution for treatment considerations. Due to the low spatial resolution of localized in vivo spectroscopy and low longitudinal resolution in relaxation and diffusion-weighted images a partial volume problem is always present. Present work attempts to overcome this problem by careful analysis of transversal relaxation rate and apparent diffusion coefficient distributions obtained by an inverse Laplace transform algorithm (ILTA).
Martin-Landrove
Miguel
M
Centro de Física Molecular y Médica, Escuela de Física, Facultad de Ciencias, Universidad Central de Venezuela, Caracas, Venezuela. mmartin@fisica.ciens.ucv.ve
D000465:Algorithms; D001932:Brain Neoplasms / Q000145:classification* / Q000175:diagnosis*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity