94
Views
4
CrossRef citations to date
0
Altmetric
Original Articles

Recognition of diffuse liver cirrhosis based on image analysis

, , &
Pages 152-159 | Received 03 Dec 2015, Accepted 19 Feb 2016, Published online: 22 Apr 2016

References

  • El-Zanaty, F. and Way, A. Egypt demographic and health survey 2008. 241; March 2009 (Egyptian Ministry of Health, El-Zanaty and Associates, and Macro International, Cairo, Egypt).
  • Saleh, D. A., Shebl, F., Abdel-Hamid, M., Narooz, S., Mikhail, N., El-Batanony, M., El-Kafrawy, S., El-Daly, M., Sharaf, S., Hashem, M., El-Kamary, S., Magder, L. S. S., Stoszek, K. and Stricklandb, G. T. Incidence and risk factors for Hepatitis C infection in a Cohort of Women in rural Egypt. T. Roy. Soc. Trop. Med. H., 2008, 102, (9), 921–928. doi: 10.1016/j.trstmh.2008.04.011
  • Zhou, S. and Wan, J. Survey of algorithms for the analysis of diffused liver disease from B-mode ultrasound images. 9th Int. Conf. on ‘Electronic measurement and instruments, ICEMI'09’, Beijing, 16–19 August 2009, IEEE, pp. 576–582.
  • Ribeiro, R., Marinho, R., Velosa, J., Ramalho, F. and Sanches, J. M. Chronic liver disease staging classification based on ultrasound, clinical and laboratorial data, 2011 IEEE Int. Symp. on ‘Biomedical imaging: from nano to macro’, Chicago, IL, 2011, IEEE, pp. 707–710.
  • Fujita, Y., Hamamoto, Y., Segawa, M., Terai, S. and Sakaida, I. An improved method for cirrhosis detection using liver's ultrasound images. 2010 20th Int. Conf. on ‘Pattern recognition (ICPR)’, Istanbul, August 2010, IEEE, pp. 2294–2297.
  • Kim, H. C., Nam, C. M., Jee, S. H., Han, K. H., Oh, D. K. and Suh, I. Normal serum aminotransferase concentration and risk of mortality from liver diseases: prospective cohort study. Brit. Med. J., 2004, 328, 1–6. doi: 10.1136/bmj.38050.593634.63
  • Pratt, D. S. and Kaplan, M. M. Evaluation of abnormal liver-enzyme results in asymptomatic patients. N. Engl. J. Med., 2000, 342, 1266–1271. doi: 10.1056/NEJM200004273421707
  • Bianchi, L. Liver biopsy in elevated liver functions tests? An old question revisited. J. Hepatol., 2001, 35, (2), 290–294. doi: 10.1016/S0168-8278(01)00155-6
  • McCullough, A. J. The clinical features, diagnosis and natural history of nonalcoholic fatty liver disease. Clin. Liver Dis., 2004, 8, (3), 521–533. doi: 10.1016/j.cld.2004.04.004
  • Ratziu, V., Charlotte, F., Heurtier, A., Gombert, S., Giral, P., Bruckert, E., Grimaldi, A., Capron, F. and Poynard, T. Sampling variability of liver biopsy in nonalcoholic fatty liver disease. Gastroenterology, 2005, 128, (7), 1898–1906. doi: 10.1053/j.gastro.2005.03.084
  • Ducommun, J. C., Goldberg, H. I., Korobkin, M., Moss, A. A. and Kressel, H. Y. The relation of liver fat to computed tomography numbers: a preliminary experimental study in rabbits. Radiology, 1979, 130, (2), 511–513. doi: 10.1148/130.2.511
  • Kawata, R., Sakata, K., Kunieda, T., Saji, S., Doi, H. and Nozawa, Y. Quantitative evaluation of fatty liver by computed tomography in rabbits. Am. J. Roentgenol., 1984, 142, (4), 741–746. doi: 10.2214/ajr.142.4.741
  • Georgoff, P., Thomasson, D., Louie, A., Fleischman, E., Dutcher, L., Mani, H., Kottilil, S., Morse, C., Dodd, L., Kleiner, D. and Hadigan, C. Hydrogen-1 MR spectroscopy for measurement and diagnosis of hepatic steatosis. Am. J. Roentgenol., 2012, 199, (1), 2–7. doi: 10.2214/AJR.11.7384
  • Pacifico, L., Celestre, M., Anania, C., Paolantonio, P., Chiesa, C. and Laghi, A. MRI and ultrasound for hepatic fat quantification: relationships to clinical and metabolic characteristics of pediatric nonalcoholic fatty liver disease. Acta Paediatr., 2007, 96, (4), 542–547. doi: 10.1111/j.1651-2227.2007.00186.x
  • Rinella, M. E., McCarthy, R., Thakrar, K., Finn, J. P., Rao, S. M., Koffron, A. J., Abecassis, M. and Blei, A. T. Dual-echo, chemical shift gradient-echo magnetic resonance imaging to quantify hepatic steatosis: implications for living liver donation. Liver Transplant., 2003, 9, (8), 851–856. doi: 10.1053/jlts.2003.50153
  • Schwenzer, N. F., Springer, F., Schraml, C., Stefan, N., Machann, J. and Schick, F. Noninvasive assessment and quantification of liver steatosis by ultrasound, computed tomography and magnetic resonance. J. Hepatol., 2009, 51, (3), 433–445. doi: 10.1016/j.jhep.2009.05.023
  • Forsberg, L., Florén, C. H., Hederström, E. and Prytz, H. Ultrasound examination in diffuse liver disease. Clinical significance of enlarged lymph nodes in the hepato-duodenal ligament. Acta Radiol., 1987, 28, (3), 281–284. doi: 10.1177/028418518702800322
  • Palmentieri, B., de Sio, I., La Mura, V., Masarone, M., Vecchione, R., Bruno, S., Torella, R. and Persico, M. The role of bright liver echo pattern on ultrasound B mode examination in the diagnosis of liver steatosis. Dig. Liver Dis., 2006, 38, (7), 485–489. doi: 10.1016/j.dld.2006.03.021
  • Gebo, K., Herlong, H., Torbenson, M., Jenckes, M., Chander, G., Ghanem, K., El-Kamary, S., Sulkowski, M. and Bass, E. Role of liver biopsy in the management of chronic hepatitis C: a systematic review. Hepatology, 2002, 36, (5), 161–172. doi: 10.1053/jhep.2002.36989
  • Piccinino, F., Sagnelli, E., Pasquale, G. and Giusti, G. Complications following percutaneous liver biopsy. A multicentre retrospective study on 68,276 biopsies. J. Hepatol., 1986, 2, (2), 165–173. doi: 10.1016/S0168-8278(86)80075-7
  • Lebrec, D., Goldfarb, G., Degott, C., Rueff, B. and Benhamou, J. P. Transvenous liver biopsy: an experience based on 1000 hepatic tissue samplings with this procedure. Gastroenterology, 1982, 83, (2), 338–340.
  • McAfee, J. H., Keeffe, E. B., Lee, R. G. and Rösch, J. Transjugular liver biopsy. Hepatology, 1992, 15, (4), 726–32. doi: 10.1002/hep.1840150429
  • Younossi, Z. M., Gramlich, T., Liu, Y. C., Matteoni, C., Petrelli, M., Goldblum, J., Rybicki, L. and McCullough, A. J. Nonalcoholic fatty liver disease: assessment of variability in pathologic interpretations. Mod. Pathol., 1998, 11, (6), 560–565.
  • Mills, P., Saverymuttu, S., Fallowfield, M., Nussey, S. and Joseph, A. E. Ultrasound in the diagnosis of granulomatous liver disease. Clin. Radiol., 1990, 41, (2), 113–115. doi: 10.1016/S0009-9260(05)80141-2
  • Ricci, C., Longo, R., Gioulis, E., Bosco, M., Pollesello, P., Masutti, F., Crocè, L. S., Paoletti, S., de Bernard, B., Tiribelli, C. and Dalla Palma, L. Noninvasive in vivo quantitative assessment of fat content in human liver. J. Hepatol., 1997, 27, (1), 108–113. doi: 10.1016/S0168-8278(97)80288-7
  • Taylor, K. J., Gorelick, F. S., Rosenfield, A. T. and Riely, C. A. Ultrasonography of alcoholic liver disease with histological correlation. Radiology, 1981, 141, (1), 157–161. doi: 10.1148/radiology.141.1.6270725
  • Valadez, E. R., Favila, R., López, M. M., Uribe, M. and Sánchez, N. M. Imaging techniques for assessing hepatic fat content in nonalcoholic fatty liver disease. Ann. Hepatol., 2008, 7, (3), 212–220.
  • Hamer, O. W., Aguirre, D. A., Casola, G., Lavine, J. E., Woenckhaus, M. and Sirlin, C. B. Fatty liver: imaging patterns and pitfalls. Radiographics, 2006, 26, (6), 1637–1653. doi: 10.1148/rg.266065004
  • Wu, Y.-H., Huang, J. and Cheng, S. Evolutionary feature construction for ultrasound image processing, its application to automatic liver disease diagnosis. Int. Conf. on ‘Complex, intelligent, and software intensive systems’, Seoul, South Korea, 30 June–2 July 2011, IEEE, pp. 565–570.
  • Kyriacou, E., Pavlopoulos, S., Koutsouris, D., Zoumpoulis, P. and Theotokas, I. Computer assisted characterization of liver tissue using image texture analysis techniques on B-scan images. Engineering in Medicine and Biology Society. Proc. 19th Annual International Conf. of the IEEE, Chicago, IL, 30 October–2 November 1997, IEEE, pp. 806–809.
  • Hassan, T. M., Elmogy, M. and Sallam, E. Medical image segmentation for liver diseases: a survey. Int. J. Comput. Appl., 2015, 118, (19), 38–44.
  • El-Rouad Radiography Center, Menouf City, El-menoufia.
  • Andrade, A., Silva, J. S., Santos, J. and Belo-Soares, P. Classifier approaches for liver steatosis using ultrasound images. CENTERIS 2012 – Conference on ENTERprise Information Systems/HCIST 2012, Int. Conf. on ‘Health and social care information systems and technologies’, Algarve, Portugal, 3–5 October, 2012, pp. 763–770 (Elsevier).
  • Sakr, A. A., Fares, M. E. and Ramadan, M. Automated focal liver lesion staging classification based on Haralick texture features and multi-SVM. Int. J. Comput. Appl., 2014, 91, (8), 17–25.

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.