Literature DB >> 23285529

Multi-organ abdominal CT segmentation using hierarchically weighted subject-specific atlases.

Robin Wolz1, Chengwen Chu, Kazunari Misawa, Kensaku Mori, Daniel Rueckert.   

Abstract

A robust automated segmentation of abdominal organs can be crucial for computer aided diagnosis and laparoscopic surgery assistance. Many existing methods are specialised to the segmentation of individual organs or struggle to deal with the variability of the shape and position of abdominal organs. We present a general, fully-automated method for multi-organ segmentation of abdominal CT scans. The method is based on a hierarchical atlas registration and weighting scheme that generates target specific priors from an atlas database by combining aspects from multi-atlas registration and patch-based segmentation, two widely used methods in brain segmentation. This approach allows to deal with high inter-subject variation while being flexible enough to be applied to different organs. Our results on a dataset of 100 CT scans compare favourable to the state-of-the-art with Dice overlap values of 94%, 91%, 66% and 94% for liver, spleen, pancreas and kidney respectively.

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Year:  2012        PMID: 23285529     DOI: 10.1007/978-3-642-33415-3_2

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  18 in total

1.  Shape-intensity prior level set combining probabilistic atlas and probability map constrains for automatic liver segmentation from abdominal CT images.

Authors:  Jinke Wang; Yuanzhi Cheng; Changyong Guo; Yadong Wang; Shinichi Tamura
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-12-08       Impact factor: 2.924

Review 2.  Artificial intelligence in assessment of hepatocellular carcinoma treatment response.

Authors:  Bradley Spieler; Carl Sabottke; Ahmed W Moawad; Ahmed M Gabr; Mustafa R Bashir; Richard Kinh Gian Do; Vahid Yaghmai; Radu Rozenberg; Marielia Gerena; Joseph Yacoub; Khaled M Elsayes
Journal:  Abdom Radiol (NY)       Date:  2021-03-31

3.  Contour-Driven Atlas-Based Segmentation.

Authors:  Christian Wachinger; Karl Fritscher; Greg Sharp; Polina Golland
Journal:  IEEE Trans Med Imaging       Date:  2015-06-09       Impact factor: 10.048

4.  Self-assessed performance improves statistical fusion of image labels.

Authors:  Frederick W Bryan; Zhoubing Xu; Andrew J Asman; Wade M Allen; Daniel S Reich; Bennett A Landman
Journal:  Med Phys       Date:  2014-03       Impact factor: 4.071

5.  Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge.

Authors:  Geert Litjens; Robert Toth; Wendy van de Ven; Caroline Hoeks; Sjoerd Kerkstra; Bram van Ginneken; Graham Vincent; Gwenael Guillard; Neil Birbeck; Jindang Zhang; Robin Strand; Filip Malmberg; Yangming Ou; Christos Davatzikos; Matthias Kirschner; Florian Jung; Jing Yuan; Wu Qiu; Qinquan Gao; Philip Eddie Edwards; Bianca Maan; Ferdinand van der Heijden; Soumya Ghose; Jhimli Mitra; Jason Dowling; Dean Barratt; Henkjan Huisman; Anant Madabhushi
Journal:  Med Image Anal       Date:  2013-12-25       Impact factor: 8.545

6.  Multi-Organ Segmentation Over Partially Labeled Datasets With Multi-Scale Feature Abstraction.

Authors:  Xi Fang; Pingkun Yan
Journal:  IEEE Trans Med Imaging       Date:  2020-10-28       Impact factor: 10.048

7.  Fully automatic detection of renal cysts in abdominal CT scans.

Authors:  Neta Blau; Eyal Klang; Nahum Kiryati; Marianne Amitai; Orith Portnoy; Arnaldo Mayer
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-03-15       Impact factor: 2.924

8.  Statistical label fusion with hierarchical performance models.

Authors:  Andrew J Asman; Alexander S Dagley; Bennett A Landman
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2014-03-21

9.  Groupwise multi-atlas segmentation of the spinal cord's internal structure.

Authors:  Andrew J Asman; Frederick W Bryan; Seth A Smith; Daniel S Reich; Bennett A Landman
Journal:  Med Image Anal       Date:  2014-02-05       Impact factor: 8.545

10.  Model-based pancreas segmentation in portal venous phase contrast-enhanced CT images.

Authors:  Matthias Hammon; Alexander Cavallaro; Marius Erdt; Peter Dankerl; Matthias Kirschner; Klaus Drechsler; Stefan Wesarg; Michael Uder; Rolf Janka
Journal:  J Digit Imaging       Date:  2013-12       Impact factor: 4.056

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