Tissue Type Identification by MRI Using Pyramidal Segmentation and Intrinsic Parameters

In Magnetic Resonance Imaging (MRI) the signal intensity depends indirectly on particular physical and chemical characteristics of the tissues being imaged. These tissue properties influence the behavior of the nuclei undergoing resonance, and their behavior is what directly affects the MRI signal. The parameters of interest that describe this behavior are the relaxation times T1 and T2, the spin density (for hydrogen, N(H)), and the microscopic (diffusion) and macroscopic (flow, motion) motional states of the nuclei. Different imaging techniques result in different responses to these MRI parameters. These parameters exist, in turn, because of certain properties of the tissues: water content, fat content, macromolecules, paramagnetic ions and flow being among the significant variables.

[1]  R L Ehman,et al.  Reproducibility of relaxation times and spin density calculated from routine MR imaging sequences: clinical study of the CNS. , 1985, AJR. American journal of roentgenology.

[2]  Ralph Bernstein,et al.  Importance of higher-order components to multispectral classification , 1982 .

[3]  R. L. Butterfield,et al.  Multispectral analysis of magnetic resonance images. , 1985, Radiology.

[4]  Theodosios Pavlidis,et al.  A hierarchical data structure for picture processing , 1975 .

[5]  W. T. Dixon.  Simple proton spectroscopic imaging. , 1984, Radiology.

[6]  J. Casida,et al.  Pyrethroid-Like Biological Activity of Compounds Lacking Cyclopropane and Ester Groupings , 1968, Science.

[7]  R. Damadian.  Tumor Detection by Nuclear Magnetic Resonance , 1971, Science.

[8]  J. Watts,et al.  Nuclear magnetic resonance imaging of mammary adenocarcinomas in the rat , 1983, Cancer.

[9]  L. Kaufman,et al.  Detectability of Hepatomas in Rat Livers by Nuclear Magnetic Resonance Imaging , 1981 .

[10]  N M Hylton,et al.  Signal to Noise in Derived NMR Images , 1984, Magnetic resonance in medicine.

[11]  Alexander Toet,et al.  Some Applications of Hierarchical Image Processing Algorithms , 1984 .

[12]  R. Moyers,et al.  Nuclear magnetic resonance studies on human breast dysplasias and neoplasms. , 1975, Journal of the National Cancer Institute.

[13]  L Kaufman,et al.  Analytical tools for magnetic resonance imaging. , 1984, Radiology.

[14]  Douglas A. Ortendahl,et al.  Tissue Characterization Using Intrinsic NMR Parameters and a Hierarchical Processing Algorithm , 1985, IEEE Transactions on Nuclear Science.

[15]  Douglas A. Ortendahl,et al.  Automated Tissue Characterization with NMR Imaging , 1984 .