Literature DB >> 23286070

Segmentation of the pectoral muscle in breast MRI using atlas-based approaches.

Albert Gubern-Mérida1, Michiel Kallenberg, Robert Martí, Nico Karssemeijer.   

Abstract

Pectoral muscle segmentation is an important step in automatic breast image analysis methods and crucial for multi-modal image registration. In breast MRI, accurate delineation of the pectoral is important for volumetric breast density estimation and for pharmacokinetic analysis of dynamic contrast enhancement. In this paper we propose and study the performance of atlas-based segmentation methods evaluating two fully automatic breast MRI dedicated strategies on a set of 27 manually segmented MR volumes. One uses a probabilistic model and the other is a multi-atlas registration based approach. The multi-atlas approach performed slightly better, with an average Dice coefficient (DSC) of 0.74, while with the much faster probabilistic method a DSC of 0.72 was obtained.

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Year:  2012        PMID: 23286070     DOI: 10.1007/978-3-642-33418-4_46

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


  10 in total

1.  Multi-atlas-based fully automatic segmentation of individual muscles in rat leg.

Authors:  Michael Sdika; Anne Tonson; Yann Le Fur; Patrick J Cozzone; David Bendahan
Journal:  MAGMA       Date:  2015-12-08       Impact factor: 2.310

2.  An atlas-based multimodal registration method for 2D images with discrepancy structures.

Authors:  Wenchao Lv; Houjin Chen; Yahui Peng; Yanfeng Li; Jupeng Li
Journal:  Med Biol Eng Comput       Date:  2018-06-04       Impact factor: 2.602

3.  Simulation of mammographic breast compression in 3D MR images using ICP-based B-spline deformation for multimodality breast cancer diagnosis.

Authors:  Julia Krüger; Jan Ehrhardt; Arpad Bischof; Heinz Handels
Journal:  Int J Comput Assist Radiol Surg       Date:  2014-01-16       Impact factor: 2.924

4.  Test-retest reliability of automated whole body and compartmental muscle volume measurements on a wide bore 3T MR system.

Authors:  Marianna S Thomas; David Newman; Olof Dahlqvist Leinhard; Bahman Kasmai; Richard Greenwood; Paul N Malcolm; Anette Karlsson; Johannes Rosander; Magnus Borga; Andoni P Toms
Journal:  Eur Radiol       Date:  2014-05-29       Impact factor: 5.315

5.  Volume measurements of individual muscles in human quadriceps femoris using atlas-based segmentation approaches.

Authors:  Arnaud Le Troter; Alexandre Fouré; Maxime Guye; Sylviane Confort-Gouny; Jean-Pierre Mattei; Julien Gondin; Emmanuelle Salort-Campana; David Bendahan
Journal:  MAGMA       Date:  2016-03-16       Impact factor: 2.310

Review 6.  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

7.  A computerized volumetric segmentation method applicable to multi-centre MRI data to support computer-aided breast tissue analysis, density assessment and lesion localization.

Authors:  Gokhan Ertas; Simon J Doran; Martin O Leach
Journal:  Med Biol Eng Comput       Date:  2016-04-22       Impact factor: 2.602

8.  Breast MRI segmentation for density estimation: Do different methods give the same results and how much do differences matter?

Authors:  Simon J Doran; John H Hipwell; Rachel Denholm; Björn Eiben; Marta Busana; David J Hawkes; Martin O Leach; Isabel Dos Santos Silva
Journal:  Med Phys       Date:  2017-07-25       Impact factor: 4.071

9.  Volumetric breast density estimation from full-field digital mammograms: a validation study.

Authors:  Albert Gubern-Mérida; Michiel Kallenberg; Bram Platel; Ritse M Mann; Robert Martí; Nico Karssemeijer
Journal:  PLoS One       Date:  2014-01-21       Impact factor: 3.240

10.  A robust statistics driven volume-scalable active contour for segmenting anatomical structures in volumetric medical images with complex conditions.

Authors:  Kuanquan Wang; Chao Ma
Journal:  Biomed Eng Online       Date:  2016-04-14       Impact factor: 2.819

  10 in total

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