SEARCH

SEARCH BY CITATION

REFERENCES

  • 1
    Duckett S. Neuroradiology. In: Lea & Febiger editor. The pathology of the aging human nervous system, 1st ed. Philadelphia: Lea & Febiger: 1991.
  • 2
    Feldman HH, Maia LF, Mackenzie IRA, Forster BB, Martzke J, Woolfenden A. Superficial siderosis: a potential diagnostic marker of cerebral amyloid angiopathy in Alzheimer disease. Stroke 2008; 39: 28942897.
  • 3
    Imaizumi T, Chiba M, Honma T, Niwa J. Detection of hemosiderin deposition by T2*-weighted MRI after subarachnoid hemorrhage. Stroke 2003; 34: 16931698.
  • 4
    Slager UT, Wagner JA. The incidence, composition, and pathological significance of intracerebral vascular deposits in the basal ganglia. Neuropahology 1956; 15: 417431.
  • 5
    Casanova MF, Araque JM. Mineralization of the basal ganglia: implications for neuropsychiatry, pathology and neuroimaging. Psychiatry Res 2003; 121: 5987.
  • 6
    Haskins B, Leslie C. Basal ganglia mineralization in psychiatry. Biol Psychiatry 1992; 31: 752753.
  • 7
    van Harskamp NJ, Rudge P, Cipolotti L. Cognitive and social impairments in patients with superficial siderosis. Brain 2005; 128: 10821092.
  • 8
    Brass SD, Chen N, Mulkern RD, Bakshi R. Magnetic resonance imaging of iron deposition in neurological disorders. Top Magn Reson Imaging 2006; 17: 3140.
  • 9
    Cordonnier C, Al-Shahi Salman R, Wardlaw J. Spontaneous brain microbleeds: systematic review, subgroup analyses and standards for study design and reporting. Brain 2007; 19882003.
  • 10
    Forstl H, Krumm B, Eden S, Kohlmeyer K. What is the psychiatric significance of bilateral basal ganglia mineralization. Biol Psychiatry 1991; 29: 827833.
  • 11
    Szumowski J, Hayflick S, Gaarder K, Bas E, Schwarz E, Ergogmus D. Assessment of iron distribution in Hallevorden-Spatz syndrome using phase imaging and relaxation rate measurements. In: Proc 17th Annual Meeting ISMRM, Honolulu; 2009 (abstract 3346).
  • 12
    Gootjes L, Teipel SJ, Zebuhr Y, et al. Regional distribution of white matter hyperintensities in vascular dementia, Alzheimer's disease and healthy aging. Dement Geriatr Cogn Disord 2004; 18: 180188.
  • 13
    Prins ND, van Straaten ECW, van Dijk EJ, et al. Measuring progression of cerebral white matter lesions on MRI: visual rating and volumetrics. Neurology 2004; 62: 15331539.
  • 14
    Wen W, Sachdev P. The topography of white matter hyperintensities on brain MRI in healthy 60- to 64-year-old individuals. NeuroImage 2004; 22: 144154.
  • 15
    Valdes-Hernandez MC, Ferguson KJ, Chapell F, Wardlaw JM. New multispectral data fusion technique in MRI for white matter lesion segmentation: method and comparison with thresholding in FLAIR images. Eur Radiol 2010; 20: 16841691.
  • 16
    Cordonnier C, Potter GM, Jackson CA, et al. Improving inter-rater agreement about brain microbleeds: development of the Brain Observer MicroBleed Scale (BOMBS). Stroke 2009; 40: 9499.
  • 17
    Jenkinson M, Bannister PR, Brady JM, Smith SM. Improved optimisation for the robust and accurate linear registration and motion correction of brain images. NeuroImage 2002; 17: 825841.
  • 18
    Foley JD, van Dam A, Feiner SK, Hughes JF. Computer graphics: principles and practice in C, 2nd ed. New York: Addison-Wesley Professional; 1996. p 11200.
  • 19
    Guillermaud R, Brady M. Estimating the bias field of MR images. IEEE Trans Med Images 1997; 16: 238251.
  • 20
    Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; 1: 307310.
  • 21
    Diaz Acosta, Beatriz. Experiments in image segmentation for automatic US license plate recognition. MSc Thesis. Virginia Polytechnic Institute and State University, Department of Computer Science, 18-6- 2004, p 104.