BRAIN TISSUES SEGMENTATION ON MR PERFUSION IMAGES USING CUSUM FILTER FOR BOUNDARY PIXELS
G.H. Jahng, K.L.L. Ostergaard, F. Calamante, “Perfusion magnetic resonance imaging: a comprehensive update on principles and techniques,” Korean Journal of Radiology, vol. 15, issue 5, pp. 554-577, 2014.
B. Lanzman, and J.J. Heit, “Advanced MRI measures of cerebral perfusion and their clinical applications,” Topics in Magnetic Resonance Imaging, vol. 26, issue 2, pp. 83-90, 2017.
K. Welker, J. Boxerman, A. Kalnin, T. Kaufmann, M. Shiroishi, M. Wintermark, “ASFNR recommendations for clinical performance of MR dynamic susceptibility contrast perfusion imaging of the brain,” American Journal of Neuroradiology, vol. 36, issue 6, pp. E41-E51, 2015.
I. Galinovic, A.C. Ostwaldt, C. Soemmer, et. al., “Automated vs manual delineations of regions of interest – a comparison in commercially available perfusion MRI software,” BMC Medical Imaging, vol. 12, no. 16, 2012, [Online]. Available from: www.biomedcentral.com/1471-2342/12/16.
S.M. Alkhimova, and O.S. Zheleznyi, “Automatizations problem for region of interest detection in perfusion magnetic resonanse imaging,” Proceedings of the Modern Directions of Theoretical and Applied Researches’2015, Odessa, Ukraine, March 17-29, 2015, vol. 1, no. 4, pp. 90-93 (in Ukrainian).
I. Galinovic, P. Brunecker, A.C. Ostwaldt, et. al., “Fully automated postprocessing carries a risk of substantial overestimation of perfusion deficits in acute stroke magnetic resonance imaging,” Cerebrovascular Diseases, vol. 31, issue 4, pp. 408-413, 2011.
S.M. Alkhimova, “Detection of perfusion ROI as a quality control in perfusion analysis,” Proceedings of the Conference Science, Research, Development. Technics and Technology, Berlin, Germany, January 30, 2018, pp. 57-59.
I. Despotovic, B. Goossens, W. Philips “MRI segmentation of the human brain: Challenges. methods, and applications,” Computational and Mathematical Methods in Medicine, vol. 2015, article ID 450341, 23 pages, 2015.
D. Selvaraj, R. Dhanasekaran, “MRI brain image segmentation techniques – A review,” Indian Journal of Computer Science and Engineering, vol. 4, issue 5, pp. 364-381, 2013.
M.A. Balafar, A.R. Ramli, M.I. Saripan, S. Mashohor, “Review of brain MRI image segmentation methods,” Artificial Intelligence Review, vol. 33, issue 3, pp. 261-274, 2010.
S. Tripathi, R.S. Anand, E. Fernandez, “A review of brain MR image segmentation techniques,” in Proceedings of the International Conference on Recent Innovations in Applied Science, Engineering & Technology (AET-2018), Mumbai, India, June 16-17, 2018, pp.62-69.
S.M. Alkhimova, and M.M. Shargan, “Optimal parameters detection for brain segmentation on MR-images,” in Proceedings of Conference on Modern Problems and Ways of their Solution in Science, Transport, Production and Education’2014, Odessa, Ukraine, June 17-28, 2014, vol. 14, pp. 92-95 (in Ukrainian).
S. Datta, P.A. Narayana, “Automated brain extraction from T2‐weighted magnetic resonance images,” Journal of Magnetic Resonance Imaging, vol. 33, issue 4, pp. 822-829, 2011.
S. Rajagopalan, R.A. Karwoski, R. Robb, “Robust fast automatic skull stripping of MRI T2 data,” Proceedings of SPIE. Medical Imaging: Image Processing, San Diego, CA, United States, February 13-17, 2005, vol. 5747, pp. 485-495.
Z. Jin, A.L. Bertozzi, “Environmental boundary tracking and estimation using multiple autonomous vehicles,” Proceedings of the 2007 46th IEEE Conference on Decision and Control, New Orleans, LA, USA, December 12-14, 2007, pp. 4918–4923.
W. Liu, Y.E. Taima, M.B. Short, A.L. Bertozzi, “Multi-scale collaborative searching through swarming,” Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics (ICINCO), Funchal, Madeira, Portugal, June 15-18, 2010, pp. 222-231.
A. Chen, T. Wittman, A.G. Tartakovsky, A.L. Bertozzi, “Image segmentation through efficient boundary sampling,” Proceedings of the 8th International Conference on Sampling Theory and Applications (SAMPTA’09), Marseille-Luminy, France, May 18-22, 2009, pp. Special-session.
A. Chen, T. Wittman, A.G. Tartakovsky, A.L. Bertozzi, “Efficient boundary tracking through sampling,” Applied Mathematics Research eXpress, vol. 2011, issue 2, pp. 182-214, 2011.
A. Chen, “Improved boundary tracking by off-boundary detection,” Proceedings of SPIE. Remote Sensing: Image and Signal Processing for Remote Sensing XVIII, Edinburgh, United Kingdom, September 24-27, 2012, vol. 8537, pp. 85370E1-7.
E.S. Page, “A test for a change in a parameter occurring at an unknown point,” Biometrika, vol. 42, issue 4, pp. 523-527, 1955.
J.M. Lucas, and R.B. Crosier, “Fast initial response for CUSUM quality-control schemes: Give your CUSUM a head start,” Technometrics, vol. 24, issue 3, pp. 199-205, 1982.
- There are currently no refbacks.