A knowledge-based technique for liver segmentation in CT data

Chedid, 1991, Prognostic factors in alcoholic liver disease, Am J Gastroenterol, 86, 210 Marsano, 2003, Diagnosis and treatment of alcoholic liver disease and its complications, Alcohol Res Health, 27, 247 Bosch, 1991, Hepatocellular carcinoma in the world: epidemiologic questions, vol. 13, 5 Lim, 2005, Segmentation of the liver using the deformable contour method on CT images, 570 Chen, 1998, An automatic diagnostic system for CT liver image classification, IEEE Trans Biomed Eng, 45, 783, 10.1109/10.678613 Saitoh, 2004, Automatic segmentation of liver region based on extracted blood vessels, Syst Comput Jpn, 35, 1, 10.1002/scj.10592 Meinzer, 2004, Computer-based surgery planning for living liver donation, Transplantation, 78, 173 Gao, 1996, Automatic liver segmentation technique for three-dimensional visualization of CT data, Radiology, 201, 359, 10.1148/radiology.201.2.8888223 Masumoto, 2003, Automated liver segmentation using multislice CT images, Syst Comput Jpn, 34, 71, 10.1002/scj.10210 Chezmar, 1988, Liver and abdominal screening in patients with cancer: CT versus MR imaging, Radiology, 168, 43, 10.1148/radiology.168.1.3380982 Soler, 2001, Fully automatic anatomical, pathological, and functional segmentation from CT scans for hepatic surgery, Comput Aid Surg, 6, 131, 10.3109/10929080109145999 Matsushita, 2005, Epithelioid hemangioendothelioma of the liver: imaging diagnosis of a rare hepatic tumor, Dig Surg, 22, 416, 10.1159/000091443 Shiffman, 2000, Medical image segmentation using analysis of isolable-contour maps, IEEE Trans Med Imaging, 19, 1064, 10.1109/42.896782 Camara, 2003, Free form deformations guided by gradient vector flow: a surface registration method in thoracic and abdominal PET-CT applications, 224 Rao, 2005, Comparison of human and automatic segmentations of kidneys from CT images, Int J Radiat Oncol Biol Phys, 61, 954, 10.1016/j.ijrobp.2004.11.014 Heimann T, Thorn M, Kunert T, Meinzer HP. New methods for leak detection and contour correction in seeded region growing segmentation. In: 20th ISPRS Congress, Istanbul 2004, International Archives of Photogrammetry and Remote Sensing, 2004; 35:317–22. Kim H, Honda S, Ishikawa S, Okuda K, Yamamoto A, Katsuragawa S. Automatic extraction of liver regions and classification of liver cirrhosis from the abdominal CT images. In: The 30th Annual Conference of the IEEE Industrial Electronics Society. 2004; 2:1086–9. Lim, 2006, Automatic liver segmentation for volume measurement in CT Images, J Vis Commun Image Represent, 17, 860, 10.1016/j.jvcir.2005.07.001 Foruzan, 2006, Automated segmentation of liver from 3D CT images, Int J Comput Assist Radiol Surg, 1, 71 Kim, 2002, CT numbers of liver and spleen in normal children, J Korean Radiol Soc, 47, 407, 10.3348/jkrs.2002.47.4.407 Piekarski, 1980, Difference between liver and spleen CT numbers in the normal adult: its usefulness in predicting the presence of diffuse liver disease, Radiology, 137, 727, 10.1148/radiology.137.3.6934563 Chan, 2001, Active contours without edges, IEEE Trans Image Process, 10, 266, 10.1109/83.902291 Nakayama, 2006, Automated hepatic volumetry for living related liver transplantation at multisection CT, Radiology, 240, 743, 10.1148/radiol.2403050850 Lee, 2007, Efficient liver segmentation using a level-set method with optimal detection of the initial liver boundary from level-set speed images, Comput Methods Program Biomed, 88, 26, 10.1016/j.cmpb.2007.07.005 Alper Selver, 2008, Patient oriented and robust automatic liver segmentation for pre-evaluation of liver transplantation, Comput Biol Med, 38, 765, 10.1016/j.compbiomed.2008.04.006 Ginneken, 2007, 3D segmentation in the clinic: a grand challenge, MICCAI, 2007, 7