Literature DB >> 23265802

Automatic multimodal 2D/3D breast image registration using biomechanical FEM models and intensity-based optimization.

T Hopp1, M Dietzel, P A Baltzer, P Kreisel, W A Kaiser, H Gemmeke, N V Ruiter.   

Abstract

Due to their different physical origin, X-ray mammography and Magnetic Resonance Imaging (MRI) provide complementary diagnostic information. However, the correlation of their images is challenging due to differences in dimensionality, patient positioning and compression state of the breast. Our automated registration takes over part of the correlation task. The registration method is based on a biomechanical finite element model, which is used to simulate mammographic compression. The deformed MRI volume can be compared directly with the corresponding mammogram. The registration accuracy is determined by a number of patient-specific parameters. We optimize these parameters--e.g. breast rotation--using image similarity measures. The method was evaluated on 79 datasets from clinical routine. The mean target registration error was 13.2mm in a fully automated setting. On basis of our results, we conclude that a completely automated registration of volume images with 2D mammograms is feasible. The registration accuracy is within the clinically relevant range and thus beneficial for multimodal diagnosis.
Copyright © 2012 Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 23265802     DOI: 10.1016/j.media.2012.10.003

Source DB:  PubMed          Journal:  Med Image Anal        ISSN: 1361-8415            Impact factor:   8.545


  13 in total

1.  Population of 224 realistic human subject-based computational breast phantoms.

Authors:  David W Erickson; Jered R Wells; Gregory M Sturgeon; Ehsan Samei; James T Dobbins; W Paul Segars; Joseph Y Lo
Journal:  Med Phys       Date:  2016-01       Impact factor: 4.071

2.  Patient-specific biomechanical model as whole-body CT image registration tool.

Authors:  Mao Li; Karol Miller; Grand Roman Joldes; Barry Doyle; Revanth Reddy Garlapati; Ron Kikinis; Adam Wittek
Journal:  Med Image Anal       Date:  2015-01-30       Impact factor: 8.545

3.  Methodology based on genetic heuristics for in-vivo characterizing the patient-specific biomechanical behavior of the breast tissues.

Authors:  M A Lago; M J Rúperez; F Martínez-Martínez; S Martínez-Sanchis; P R Bakic; C Monserrat
Journal:  Expert Syst Appl       Date:  2015-11-30       Impact factor: 6.954

4.  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

5.  Finite-element modeling of compression and gravity on a population of breast phantoms for multimodality imaging simulation.

Authors:  Gregory M Sturgeon; Nooshin Kiarashi; Joseph Y Lo; E Samei; W P Segars
Journal:  Med Phys       Date:  2016-05       Impact factor: 4.071

6.  Robust 3D-2D image registration: application to spine interventions and vertebral labeling in the presence of anatomical deformation.

Authors:  Yoshito Otake; Adam S Wang; J Webster Stayman; Ali Uneri; Gerhard Kleinszig; Sebastian Vogt; A Jay Khanna; Ziya L Gokaslan; Jeffrey H Siewerdsen
Journal:  Phys Med Biol       Date:  2013-11-18       Impact factor: 3.609

7.  A Regression Model for Predicting Shape Deformation after Breast Conserving Surgery.

Authors:  Hooshiar Zolfagharnasab; Sílvia Bessa; Sara P Oliveira; Pedro Faria; João F Teixeira; Jaime S Cardoso; Hélder P Oliveira
Journal:  Sensors (Basel)       Date:  2018-01-09       Impact factor: 3.576

8.  A neural network-based 2D/3D image registration quality evaluator for pediatric patient setup in external beam radiotherapy.

Authors:  Jian Wu; Zhong Su; Zuofeng Li
Journal:  J Appl Clin Med Phys       Date:  2016-01-08       Impact factor: 2.102

9.  Identification of Breast Cancer Using Integrated Information from MRI and Mammography.

Authors:  Shih-Neng Yang; Fang-Jing Li; Yen-Hsiu Liao; Yueh-Sheng Chen; Wu-Chung Shen; Tzung-Chi Huang
Journal:  PLoS One       Date:  2015-06-09       Impact factor: 3.240

10.  An Anthropometric-Based Subject-Specific Finite Element Model of the Human Breast for Predicting Large Deformations.

Authors:  Silvia Pianigiani; Leonardo Ruggiero; Bernardo Innocenti
Journal:  Front Bioeng Biotechnol       Date:  2015-12-24
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