139
Views
3
CrossRef citations to date
0
Altmetric
General articles

A collaborative contour detector by gradient and active contours for ultrasound kidney images

, &
Pages 1292-1312 | Received 21 Mar 2017, Accepted 23 May 2018, Published online: 01 Aug 2018

References

  • A. Alam, N.K. Dahl, J.H Lipschutz, S. Rossetti, P. Smith, D. Sapir, J. Weinstein, P.M. Farlane, and D.G. Bichet, Total kidney volume in autosomal dominant polycystic kidney disease: A biomarker of disease progression and therapeutic efficacy, Am. J. Kidney. Dis. 66(4) (2015), pp. 564–576. doi: 10.1053/j.ajkd.2015.01.030
  • H.R. Arabnia and Q. Tran, Emerging Trends in Applications and Infrastructures for Computational Biology, Bioinformatics, and Systems Biology: Systems and Applications, Morgan Kaufmann, Burlington, MA, 2016.
  • Y.Y. Boykov and M-P. Jolly, Interactive graph cuts for optimal boundary & region segmentation of objects in nd images. Computer Vision, 2001. ICCV 2001. Proceedings. Eighth IEEE International Conference on, Vol. 1, pp. 105–112. IEEE, 2001.
  • J. Canny, A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell, 2(6) (1986), pp. 679–698.
  • J.J. Cerrolaza, N. Safdar, C.A. Peters, E. Myers, J. Jago, and M. Linguraru, Segmentation of kidney in 3d-ultrasound images using gabor-based appearance models.2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI), pp. 633–636. IEEE, 2014.
  • Y.T. Chow, K. Ito, K. Liu, and J. Zou, Direct sampling method for diffusive optical tomography, SIAM. J. Sci. Comput. 37(4) (2015), pp. A1658–A1684. doi: 10.1137/14097519X
  • Y.T. Chow, K. Ito and J. Zou, A direct sampling method for electrical impedance tomography, Inverse. Probl. 30(9) (2014), pp. 095003. doi: 10.1088/0266-5611/30/9/095003
  • Y.T. Chow, K. Ito and J. Zou, Analysis on a nonnegative matrix factorization and its applications, SIAM. J. Sci. Comput. 38(5) (2016), pp. B645–B684. doi: 10.1137/15M1020824
  • L.D. Cohen, On active contour models and balloons, CVGIP 53(2) (1991), pp. 211–218. doi: 10.1016/1049-9660(91)90028-N
  • A. Evans, P. Whelehan, K. Thomson, D. McLean, K. Brauer, C. Purdie, L. Jordan, L. Baker, and A. Thompson, Quantitative shear wave ultrasound elastography: Initial experience in solid breast masses, Breast. Cancer. Res. 12(6) (2010), p. 1. doi: 10.1186/bcr2787
  • W. Fu, M. Johnston and M. Zhang, Genetic programming for edge detection based on figure of merit. Proceedings of the 14th Annual Conference Companion on Genetic and Evolutionary Computation, pp. 1483–1484. ACM, 2012.
  • R. Gonzalez and R. Woods, Digital Image Processing, 3rd ed., Prentice Hall, Upper Saddle River, NJ, 2007.
  • J.J. Grantham and V.E. Torres, The importance of total kidney volume in evaluating progression of polycystic kidney disease, Nat. Rev. Nephrology 12(11) (2016), pp. 667–677. doi: 10.1038/nrneph.2016.135
  • C. Harris and M. Stephens, A combined corner and edge detector. Alvey Vision Conference, Vol. 15, p. 50. Citeseer, 1988.
  • K. Ito, B. Jin, and J. Zou, A direct sampling method to an inverse medium scattering problem, Inverse. Probl. 28(2) (2012), p. 025003. doi: 10.1088/0266-5611/28/2/025003
  • J. Ivins and J. Porrill, Everything you always wanted to know about snakes (but were afraid to ask), Artif. Intell. 2000 (1995), pp. 86–98.
  • M. Kass, A. Witkin, and D. Terzopoulos, Snakes: Active contour models, Int. J. Comput. Vis. 1(4) (1988), pp. 321–331. doi: 10.1007/BF00133570
  • C. Ke, C. Shieh, W. Hwang, and A. Ziviani, A two markers system for improved mpeg video delivery in a diffserv network, IEEE. Commun. Lett. 9(4) (2005), pp. 381–383. doi: 10.1109/LCOMM.2005.1413641
  • M. Martín and C. Alberola, A bayesian approach to in vivo kidney ultrasound contour detection using Markov random fields. International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 397–404. Springer, 2002.
  • M. Martın-Fernández and C. Alberola-Lopez, An approach for contour detection of human kidneys from ultrasound images using markov random fields and active contours, Med. Image. Anal. 9(1) (2005), pp. 1–23. doi: 10.1016/j.media.2004.05.001
  • C. Mendoza, X. Kang, N. Safdar, E. Myers, A. Martin, E. Grisan, C.A. Peters, and M. Linguraru, Automatic analysis of pediatric renal ultrasound using shape, anatomical and image acquisition priors. International Conference on Medical Image Computing and Computer-Assisted Intervention, pages 259–266. Springer, 2013.
  • C.S. Mendoza, X. Kang, N. Safdar, E. Myers, C.A. Peters and M.G. Linguraru, Kidney segmentation in ultrasound via genetic initialization and active shape models with rotation correction. 2013 IEEE 10th International Symposium on Biomedical Imaging, pp. 69–72. IEEE, 2013.
  • J.A. Noble and D. Boukerroui, Ultrasound image segmentation: a survey, IEEE. Trans. Med. Imaging. 25(8) (2006), pp. 987–1010. doi: 10.1109/TMI.2006.877092
  • S. Osher and R. Fedkiw, Level set Methods and Dynamic Implicit Surfaces, Vol. 153, Springer Science & Business Media, Berlin, Germany, 2006.
  • A. Perperidis, Postprocessing approaches for the improvement of cardiac ultrasound b-mode images: A review, IEEE. Trans. Ultrason. Ferroelectr. Freq. Control. 63(3) (2016), pp. 470–485. doi: 10.1109/TUFFC.2016.2526670
  • A. Sarti, C. Corsi, E. Mazzini, and C. Lamberti, Maximum likelihood segmentation of ultrasound images with rayleigh distribution, IEEE. Trans. Ultrason. Ferroelectr. Freq. Control. 52(6) (2005), pp. 947–960. doi: 10.1109/TUFFC.2005.1504017
  • T.A. Tuthill, R.H Sperry, and K.J. Parker, Deviations from rayleigh statistics in ultrasonic speckle, Ultrason. Imaging. 10(2) (1988), pp. 81–89. doi: 10.1177/016173468801000201
  • C. Woon, A. Bielinski-Bradbury, K. O'Reilly, and P. Robinson, A systematic review of the predictors of disease progression in patients with autosomal dominant polycystic kidney disease, BMC. Nephrol. 16(1) (2015), pp. 1. doi: 10.1186/s12882-015-0114-5
  • F. Yi and I. Moon, Image segmentation: A survey of graph-cut methods. Systems and Informatics (ICSAI), 2012 International Conference on, pp. 1936–1941. IEEE, 2012.
  • H. Zhi, B. Ou, B. Luo, X. Feng, Y. Wen, and H. Yang, Comparison of ultrasound elastography, mammography, and sonography in the diagnosis of solid breast lesions, J. Ultrasound. Med. 26(6) (2007), pp. 807–815. doi: 10.7863/jum.2007.26.6.807

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.