Literature DB >> 27254856

Evaluation of Six Registration Methods for the Human Abdomen on Clinically Acquired CT.

Zhoubing Xu, Christopher P Lee, Mattias P Heinrich, Marc Modat, Daniel Rueckert, Sebastien Ourselin, Richard G Abramson, Bennett A Landman.   

Abstract

OBJECTIVE: This work evaluates current 3-D image registration tools on clinically acquired abdominal computed tomography (CT) scans.
METHODS: Thirteen abdominal organs were manually labeled on a set of 100 CT images, and the 100 labeled images (i.e., atlases) were pairwise registered based on intensity information with six registration tools (FSL, ANTS-CC, ANTS-QUICK-MI, IRTK, NIFTYREG, and DEEDS). The Dice similarity coefficient (DSC), mean surface distance, and Hausdorff distance were calculated on the registered organs individually. Permutation tests and indifference-zone ranking were performed to examine the statistical and practical significance, respectively.
RESULTS: The results suggest that DEEDS yielded the best registration performance. However, due to the overall low DSC values, and substantial portion of low-performing outliers, great care must be taken when image registration is used for local interpretation of abdominal CT.
CONCLUSION: There is substantial room for improvement in image registration for abdominal CT. SIGNIFICANCE: All data and source code are available so that innovations in registration can be directly compared with the current generation of tools without excessive duplication of effort.

Entities:  

Mesh:

Year:  2016        PMID: 27254856      PMCID: PMC4972188          DOI: 10.1109/TBME.2016.2574816

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  27 in total

1.  Nonrigid registration using free-form deformations: application to breast MR images.

Authors:  D Rueckert; L I Sonoda; C Hayes; D L Hill; M O Leach; D J Hawkes
Journal:  IEEE Trans Med Imaging       Date:  1999-08       Impact factor: 10.048

2.  Label fusion in atlas-based segmentation using a selective and iterative method for performance level estimation (SIMPLE).

Authors:  Thomas Robin Langerak; Uulke A van der Heide; Alexis N T J Kotte; Max A Viergever; Marco van Vulpen; Josien P W Pluim
Journal:  IEEE Trans Med Imaging       Date:  2010-07-26       Impact factor: 10.048

3.  Diffeomorphic demons: efficient non-parametric image registration.

Authors:  Tom Vercauteren; Xavier Pennec; Aymeric Perchant; Nicholas Ayache
Journal:  Neuroimage       Date:  2008-11-07       Impact factor: 6.556

4.  Efficient multi-atlas abdominal segmentation on clinically acquired CT with SIMPLE context learning.

Authors:  Zhoubing Xu; Ryan P Burke; Christopher P Lee; Rebeccah B Baucom; Benjamin K Poulose; Richard G Abramson; Bennett A Landman
Journal:  Med Image Anal       Date:  2015-05-21       Impact factor: 8.545

5.  Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge.

Authors:  Keelin Murphy; Bram van Ginneken; Joseph M Reinhardt; Sven Kabus; Kai Ding; Xiang Deng; Kunlin Cao; Kaifang Du; Gary E Christensen; Vincent Garcia; Tom Vercauteren; Nicholas Ayache; Olivier Commowick; Grégoire Malandain; Ben Glocker; Nikos Paragios; Nassir Navab; Vladlena Gorbunova; Jon Sporring; Marleen de Bruijne; Xiao Han; Mattias P Heinrich; Julia A Schnabel; Mark Jenkinson; Cristian Lorenz; Marc Modat; Jamie R McClelland; Sébastien Ourselin; Sascha E A Muenzing; Max A Viergever; Dante De Nigris; D Louis Collins; Tal Arbel; Marta Peroni; Rui Li; Gregory C Sharp; Alexander Schmidt-Richberg; Jan Ehrhardt; René Werner; Dirk Smeets; Dirk Loeckx; Gang Song; Nicholas Tustison; Brian Avants; James C Gee; Marius Staring; Stefan Klein; Berend C Stoel; Martin Urschler; Manuel Werlberger; Jef Vandemeulebroucke; Simon Rit; David Sarrut; Josien P W Pluim
Journal:  IEEE Trans Med Imaging       Date:  2011-05-31       Impact factor: 10.048

6.  Automated segmentation and quantification of liver and spleen from CT images using normalized probabilistic atlases and enhancement estimation.

Authors:  Marius George Linguraru; Jesse K Sandberg; Zhixi Li; Furhawn Shah; Ronald M Summers
Journal:  Med Phys       Date:  2010-02       Impact factor: 4.071

7.  Abdominal multi-organ CT segmentation using organ correlation graph and prediction-based shape and location priors.

Authors:  Toshiyuki Okada; Marius George Linguraru; Masatoshi Hori; Ronald M Summers; Noriyuki Tomiyama; Yoshinobu Sato
Journal:  Med Image Comput Comput Assist Interv       Date:  2013

8.  SIMPLE is a good idea (and better with context learning).

Authors:  Zhoubing Xu; Andrew J Asman; Peter L Shanahan; Richard G Abramson; Bennett A Landman
Journal:  Med Image Comput Comput Assist Interv       Date:  2014

Review 9.  Multi-atlas segmentation of biomedical images: A survey.

Authors:  Juan Eugenio Iglesias; Mert R Sabuncu
Journal:  Med Image Anal       Date:  2015-07-06       Impact factor: 8.545

Review 10.  FSL.

Authors:  Mark Jenkinson; Christian F Beckmann; Timothy E J Behrens; Mark W Woolrich; Stephen M Smith
Journal:  Neuroimage       Date:  2011-09-16       Impact factor: 6.556

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  21 in total

1.  TernaryNet: faster deep model inference without GPUs for medical 3D segmentation using sparse and binary convolutions.

Authors:  Mattias P Heinrich; Max Blendowski; Ozan Oktay
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-05-30       Impact factor: 2.924

2.  Robust Multicontrast MRI Spleen Segmentation for Splenomegaly Using Multi-Atlas Segmentation.

Authors:  Yuankai Huo; Jiaqi Liu; Zhoubing Xu; Robert L Harrigan; Albert Assad; Richard G Abramson; Bennett A Landman
Journal:  IEEE Trans Biomed Eng       Date:  2018-02       Impact factor: 4.538

3.  Discontinuity Preserving Liver MR Registration with 3D Active Contour Motion Segmentation.

Authors:  Dongxiao Li; Wenxiong Zhong; Kofi M Deh; Thanh Nguyen; Martin R Prince; Yi Wang; Pascal Spincemaille
Journal:  IEEE Trans Biomed Eng       Date:  2018-11-12       Impact factor: 4.538

4.  Memory-efficient 2.5D convolutional transformer networks for multi-modal deformable registration with weak label supervision applied to whole-heart CT and MRI scans.

Authors:  Alessa Hering; Sven Kuckertz; Stefan Heldmann; Mattias P Heinrich
Journal:  Int J Comput Assist Radiol Surg       Date:  2019-09-19       Impact factor: 2.924

5.  Learning-based three-dimensional registration with weak bounding box supervision.

Authors:  Mona Schumacher; Hanna Siebert; Andreas Genz; Ragnar Bade; Mattias Heinrich
Journal:  J Med Imaging (Bellingham)       Date:  2022-07-14

6.  DiffeoRaptor: diffeomorphic inter-modal image registration using RaPTOR.

Authors:  Nima Masoumi; Hassan Rivaz; M Omair Ahmad; Yiming Xiao
Journal:  Int J Comput Assist Radiol Surg       Date:  2022-09-29       Impact factor: 3.421

7.  Fully Automated Abdominal CT Biomarkers for Type 2 Diabetes Using Deep Learning.

Authors:  Perry J Pickhardt; Ronald M Summers; Hima Tallam; Daniel C Elton; Sungwon Lee; Paul Wakim
Journal:  Radiology       Date:  2022-04-05       Impact factor: 29.146

8.  Multiresolution image registration for multimodal brain images and fusion for better neurosurgical planning.

Authors:  Siddeshappa Nandish; Gopalakrishna Prabhu; Kadavigere V Rajagopal
Journal:  Biomed J       Date:  2017-12-27       Impact factor: 4.910

9.  Automatic Multi-Organ Segmentation on Abdominal CT With Dense V-Networks.

Authors:  Eli Gibson; Francesco Giganti; Yipeng Hu; Ester Bonmati; Steve Bandula; Kurinchi Gurusamy; Brian Davidson; Stephen P Pereira; Matthew J Clarkson; Dean C Barratt
Journal:  IEEE Trans Med Imaging       Date:  2018-02-14       Impact factor: 10.048

10.  Domain adaptation for segmentation of critical structures for prostate cancer therapy.

Authors:  Anneke Meyer; Alireza Mehrtash; Marko Rak; Oleksii Bashkanov; Bjoern Langbein; Alireza Ziaei; Adam S Kibel; Clare M Tempany; Christian Hansen; Junichi Tokuda
Journal:  Sci Rep       Date:  2021-06-01       Impact factor: 4.379

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