Computation and management of weighted activation vectors in support to fMRI analysis of clinical subjects

References

• Aggarwal CC, Hinneburg A, Keim DA . 2001, On the surprising behavior of distance metrics in high dimensional space. Van Den Bussche J, Vianu V editors, Database theory — ICDT 2001. Lect Notes Comput Sc. Berlin: Springer; p. 420–434.
   Google Scholar
• Buxton RB, Wong EC, Frank LR. 1998. Dynamics of blood flow and oxygenation changes during brain activation: the balloon model. Magn Reson Med. 39(6):855–864.
   PubMed Web of Science ®Google Scholar
• Cox RW. 1996. AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput Biomed Res. 29(3):162–173.
   PubMedGoogle Scholar
• Cuadra MB, Pollo C, Bardera A, Cuisenaire O, Villemure JG, Thiran JP. 2004. Atlas-based segmentation of pathological MR brain images using a model of lesion growth. IEEE Trans Med Imaging. 23(10):1301–1314.
   PubMed Web of Science ®Google Scholar
• Davies DL, Bouldin DW. 1979. A cluster separation measure. IEEE Trans Pattern Anal Mach Intell. 2:224–227.
   Web of Science ®Google Scholar
• De Benedictis A, Duffau H. 2011. Brain hodotopy: from esoteric concept to practical surgical applications. J Neurosurg. 68(6):1709–1723.
   Google Scholar
• Desikan RS, Ségonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, Buckner RL, Dale AM, Maguire RP, Bradley TH, et al. 2006. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage. 31(3):968–980.
   PubMed Web of Science ®Google Scholar
• Eickhoff SB, Heim S, Zilles K, Amunts K. 2006. Testing anatomically specified hypotheses in functional imaging using cytoarchitectonic maps. Neuroimage. 32(2):570–582.
   PubMed Web of Science ®Google Scholar
• Eickhoff SB, Paus T, Caspers S, Grosbras MH, Evans AC, Zilles K, Amunts K. 2007. Assignment of functional activations to probabilistic cytoarchitectonic areas revisited. Neuroimage. 36(3):511–521.
   PubMed Web of Science ®Google Scholar
• Eickhoff SB, Stephan KE, Mohlberg H, Grefkes C, Fink GR, Amunts K, Zilles K. 2005. A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data. Neuroimage. 25(4):1325–1335.
   PubMed Web of Science ®Google Scholar
• Frazier JA, Chiu S, Breeze JL, Makris N, Lange N, Kennedy DN, Herbert MR, Bent EK, Koneru VK, Dieterich ME. 2005. Structural brain magnetic resonance imaging of limbic and thalamic volumes in pediatric bipolar disorder. Am J Psychiatry. 162(7):1256–1265.
   PubMed Web of Science ®Google Scholar
• Friston KJ, Holmes AP, Worsley KJ, Poline JP, Frith CD, Frackowiak RS. 1994. Statistical parametric maps in functional imaging: A general linear approach. Hum Brain Mapp. 2(4):189–210.
   Google Scholar
• Fritzke B. 1994. Growing cell structures - a self-organizing network for unsupervised and supervised learning. Neural Netw. 7(9):1441–1460.
   Web of Science ®Google Scholar
• Goldstein JM, Seidman LJ, Makris N, Ahern T, O’Brien LM, Caviness VS Jr, Kennedy DN, Faraone SV, Tsuang MT. 2007. Hypothalamic abnormalities in schizophrenia: sex effects and genetic vulnerability. Biol Psychiatry. 61(8):935–945.
   PubMed Web of Science ®Google Scholar
• Hill DL, Batchelor PG, Holden M, Hawkes DJ. 2001. Medical image registration. Phys Med Biol. 46:3.
   Web of Science ®Google Scholar
• Jenkinson M, Beckmann CF, Behrens TE, Woolrich MW, Smith SM. 2012. Fsl. Neuroimage. 62(2):782–790.
   PubMed Web of Science ®Google Scholar
• Kohonen T. 1968. The self-organizing map. Neurocomputing. 21(1):1–6.
   Google Scholar
• Kroon DJ, Slump CH 2009. MRI modalitiy transformation in demon registration. In: Proceedings of IEEE International Symposium on Biomedical Imaging: From Nano to Macro June 28 - July 1; Boston,(MA). Piscataway (NJ): IEEE Press. p. 963–966.
   Google Scholar
• Lachiche N, Hommet J, Korczak J, Braud A . 2005, Neuronal clustering of brain fmri images. Pal SK, Bandyopadhyay S, Biswas S editors, PReMI 2005. Lect Notes Comput Sc. Berlin: Springer; p. 300–305.
   Google Scholar
• Lindquist MA. 2008. The statistical analysis of fMRI data. Stat Sci. 23(4):439–464.
   Web of Science ®Google Scholar
• Luo WL, Nichols TE. 2003. Diagnosis and exploration of massively univariate neuroimaging models. Neuroimage. 19(3):1014–1032.
   PubMed Web of Science ®Google Scholar
• Maintz JB, Viergever MA. 1998. A survey of medical image registration. Med Image Anal. 2(1):1–36.
   PubMedGoogle Scholar
• Makris N, Goldstein JM, Kennedy D, Hodge SM, Caviness VS, Faraone SV, Tsuang MT, Seidman LJ. 2006. Decreased volume of left and total anterior insular lobule in schizophrenia. Schizophr Res. 83(2):155–171.
   PubMed Web of Science ®Google Scholar
• Martelli A. 1972. Edge detection using heuristic search methods. Comput Gr Image Process. 1(2):169–182.
   Google Scholar
• Miller GA. 1956. The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychol Rev. 63(2):81–97.
   PubMed Web of Science ®Google Scholar
• Pedoia V, Binaghi E. 2013. Automatic MRI 2D brain segmentation using graph searching technique. Int J Numer Method Biomed Eng. 29(9):887–904.
   PubMed Web of Science ®Google Scholar
• Pedoia V, De Benedictis A, Renis G, Monti E, Balbi S, Binaghi E. 2012. Manual labeling strategy for ground truth estimation in MRI glial tumor segmentation. In VIGTA 2012. Proceedings of the 1st International Workshop on Visual Interfaces for Ground Truth Collection in Computer Vision Applications; May 21–21; Capri. New York (NY): ACM. p. 8: 1–8:4.
   Google Scholar
• Pedoia V, Gallo I, Binaghi E. 2011. Affine SPHARM registration-neural estimation of affine transformation in spherical domain. In: Mestetskiy L, Braz J, editors. VISAPP 2011. Vilamoura: SciTePress Digital Library; p. 197–200, March 5–7.
   Google Scholar
• R Development Core Team. 2008. R: A language and environment for statistical computing. Vienna (Austria): R Foundation for Statistical Computing. ISBN:3–900051–07–0. http://www.R-project.org.
   Google Scholar
• Simon HA. 1991. Bounded rationality and organizational learning. Organ Sci. 2(1):125–134.
   Web of Science ®Google Scholar
• Solomon J, Raymont V, Braun A, Butman JA, Grafman J. 2007. User-friendly software for the analysis of brain lesions (ABLe). Comput Methods Programs Biomed. 86(3):245–254.
   PubMed Web of Science ®Google Scholar
• Vergani A, Martinelli S, Binaghi E 2017. Cluster analysis of functional neuroimages using data reduction and competitive learning algorithms. In: Tavares JM, Jorge NRM. (editors). VipIMAGE 2017. Proceedings of the VI ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing, Lecture Notes in Computational Vision and Biomechanics. October 18–20; Porto. Berlin: Springer International Publishing. p: 62–71.
   Google Scholar
• Vergani A, Minotto R, Strocchi S, Binaghi E 2018. Quantitative relations of craiim human brain atlases. In: Simidjievski N, Santuy A, Menzel M, Tanevski J, Karasenko V, Mahfoud T, Tipotsch V, Rass T, Saria A, (editors). 1st Human Brain Project Student Conference 2017. Vienna: Frontiers Media SA, p.60–68.
   Google Scholar
• Vesanto J, Alhoniemi E. 2000. Clustering of the self-organizing map. IEEE Trans Neural Netw. 11(3):586–600.
   PubMed Web of Science ®Google Scholar
• Wikibooks contributors. SPM [Internet]. Wikibooks, The Free Textbook Project; 2017 Sep 19, 09:56 UTC accessed 2017 Dec 4. https://en.wikibooks.org/w/index.php?title=SPM&oldid=3296302.
   Google Scholar
• Wismüller A, Meyer-Bäse A, Lange O, Auer D, Reiser MF, Sumners D. 2004. Model-free functional MRI analysis based on unsupervised clustering. J Biomed Inform. 37(1):10–18.
   PubMed Web of Science ®Google Scholar
• Worsley KJ, Friston KJ. 1995. Analysis of fMRI time-series revisited—again. Neuroimage. 2(3):173–181.
   PubMed Web of Science ®Google Scholar
• Worsley KJ, Taylor JE, Tomaiuolo F, Lerch J. 2004. Unified univariate and multivariate random field theory. Neuroimage. 23:S189–S195.
   PubMed Web of Science ®Google Scholar