Literature DB >> 24110354

Computerized segmentation of liver in hepatic CT and MRI by means of level-set geodesic active contouring.

Kenji Suzuki, Hieu Trung Huynh, Yipeng Liu, Dominic Calabrese, Karen Zhou, Aytekin Oto, Masatoshi Hori.   

Abstract

Computerized liver volumetry has been studied, because the current "gold-standard" manual volumetry is subjective and very time-consuming. Liver volumetry is done in either CT or MRI. A number of researchers have developed computerized liver segmentation in CT, but there are fewer studies on ones for MRI. Our purpose in this study was to develop a general framework for liver segmentation in both CT and MRI. Our scheme consisted of 1) an anisotropic diffusion filter to reduce noise while preserving liver structures, 2) a scale-specific gradient magnitude filter to enhance liver boundaries, 3) a fast-marching algorithm to roughly determine liver boundaries, and 4) a geodesic-active-contour model coupled with a level-set algorithm to refine the initial boundaries. Our CT database contained hepatic CT scans of 18 liver donors obtained under a liver transplant protocol. Our MRI database contains 23 patients with 1.5T MRI scanners. To establish "gold-standard" liver volumes, radiologists manually traced the contour of the liver on each CT or MR slice. We compared our computer volumetry with "gold-standard" manual volumetry. Computer volumetry in CT and MRI reached excellent agreement with manual volumetry (intra-class correlation coefficient = 0.94 and 0.98, respectively). Average user time for computer volumetry in CT and MRI was 0.57 ± 0.06 and 1.0 ± 0.13 min. per case, respectively, whereas those for manual volumetry were 39.4 ± 5.5 and 24.0 ± 4.4 min. per case, respectively, with statistically significant difference (p < .05). Our computerized liver segmentation framework provides an efficient and accurate way of measuring liver volumes in both CT and MRI.

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Year:  2013        PMID: 24110354      PMCID: PMC4283827          DOI: 10.1109/EMBC.2013.6610167

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  17 in total

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2.  A fast marching level set method for monotonically advancing fronts.

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Journal:  Proc Natl Acad Sci U S A       Date:  1996-02-20       Impact factor: 11.205

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Journal:  Med Phys       Date:  2012-03       Impact factor: 4.071

4.  A fully automatic three-step liver segmentation method on LDA-based probability maps for multiple contrast MR images.

Authors:  Oliver Gloger; Jens Kühn; Adam Stanski; Henry Völzke; Ralf Puls
Journal:  Magn Reson Imaging       Date:  2010-04-21       Impact factor: 2.546

5.  Liver segmentation for contrast-enhanced MR images using partitioned probabilistic model.

Authors:  László Ruskó; György Bekes
Journal:  Int J Comput Assist Radiol Surg       Date:  2010-06-11       Impact factor: 2.924

6.  Living donor right liver lobes: preoperative CT volumetric measurement for calculation of intraoperative weight and volume.

Authors:  Arne-Jörn Lemke; Martin Julius Brinkmann; Thomas Schott; Stefan Markus Niehues; Utz Settmacher; Peter Neuhaus; Roland Felix
Journal:  Radiology       Date:  2006-07-25       Impact factor: 11.105

7.  Preoperative volume prediction in adult living donor liver transplantation: how much can we rely on it?

Authors:  A Radtke; G C Sotiropoulos; S Nadalin; E P Molmenti; T Schroeder; H Lang; F Saner; C Valentin-Gamazo; A Frilling; A Schenk; C E Broelsch; M Malagó
Journal:  Am J Transplant       Date:  2007-01-04       Impact factor: 8.086

8.  Automatic liver segmentation technique for three-dimensional visualization of CT data.

Authors:  L Gao; D G Heath; B S Kuszyk; E K Fishman
Journal:  Radiology       Date:  1996-11       Impact factor: 11.105

9.  Quantitative radiology: automated CT liver volumetry compared with interactive volumetry and manual volumetry.

Authors:  Kenji Suzuki; Mark L Epstein; Ryan Kohlbrenner; Shailesh Garg; Masatoshi Hori; Aytekin Oto; Richard L Baron
Journal:  AJR Am J Roentgenol       Date:  2011-10       Impact factor: 3.959

10.  Patient oriented and robust automatic liver segmentation for pre-evaluation of liver transplantation.

Authors:  M Alper Selver; Aykut Kocaoğlu; Güleser K Demir; Hatice Doğan; Oğuz Dicle; Cüneyt Güzeliş
Journal:  Comput Biol Med       Date:  2008-06-11       Impact factor: 4.589

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  3 in total

1.  Liver volumetry: Is imaging reliable? Personal experience and review of the literature.

Authors:  Mirko D'Onofrio; Riccardo De Robertis; Emanuele Demozzi; Stefano Crosara; Stefano Canestrini; Roberto Pozzi Mucelli
Journal:  World J Radiol       Date:  2014-04-28

2.  A Unified Level Set Framework Combining Hybrid Algorithms for Liver and Liver Tumor Segmentation in CT Images.

Authors:  Zhou Zheng; Xuechang Zhang; Huafei Xu; Wang Liang; Siming Zheng; Yueding Shi
Journal:  Biomed Res Int       Date:  2018-08-09       Impact factor: 3.411

Review 3.  Artificial Intelligence in hepatology, liver surgery and transplantation: Emerging applications and frontiers of research.

Authors:  Fadl H Veerankutty; Govind Jayan; Manish Kumar Yadav; Krishnan Sarojam Manoj; Abhishek Yadav; Sindhu Radha Sadasivan Nair; T U Shabeerali; Varghese Yeldho; Madhu Sasidharan; Shiraz Ahmad Rather
Journal:  World J Hepatol       Date:  2021-12-27
  3 in total

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