Literature DB >> 24727358

MRI to X-ray mammography intensity-based registration with simultaneous optimisation of pose and biomechanical transformation parameters.

Thomy Mertzanidou1, John Hipwell2, Stian Johnsen2, Lianghao Han2, Bjoern Eiben2, Zeike Taylor3, Sebastien Ourselin2, Henkjan Huisman4, Ritse Mann5, Ulrich Bick6, Nico Karssemeijer4, David Hawkes2.   

Abstract

Determining corresponding regions between an MRI and an X-ray mammogram is a clinically useful task that is challenging for radiologists due to the large deformation that the breast undergoes between the two image acquisitions. In this work we propose an intensity-based image registration framework, where the biomechanical transformation model parameters and the rigid-body transformation parameters are optimised simultaneously. Patient-specific biomechanical modelling of the breast derived from diagnostic, prone MRI has been previously used for this task. However, the high computational time associated with breast compression simulation using commercial packages, did not allow the optimisation of both pose and FEM parameters in the same framework. We use a fast explicit Finite Element (FE) solver that runs on a graphics card, enabling the FEM-based transformation model to be fully integrated into the optimisation scheme. The transformation model has seven degrees of freedom, which include parameters for both the initial rigid-body pose of the breast prior to mammographic compression, and those of the biomechanical model. The framework was tested on ten clinical cases and the results were compared against an affine transformation model, previously proposed for the same task. The mean registration error was 11.6±3.8mm for the CC and 11±5.4mm for the MLO view registrations, indicating that this could be a useful clinical tool.
Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Breast imaging; FEM-based transformation model; Mammography; Multimodal registration

Mesh:

Year:  2014        PMID: 24727358     DOI: 10.1016/j.media.2014.03.003

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


  8 in total

1.  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

2.  A framework for automatic creation of gold-standard rigid 3D-2D registration datasets.

Authors:  Hennadii Madan; Franjo Pernuš; Boštjan Likar; Žiga Špiclin
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-09-21       Impact factor: 2.924

3.  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

4.  Diagnosis of Breast Cancer Using Radiomics Models Built Based on Dynamic Contrast Enhanced MRI Combined With Mammography.

Authors:  You-Fan Zhao; Zhongwei Chen; Yang Zhang; Jiejie Zhou; Jeon-Hor Chen; Kyoung Eun Lee; Freddie J Combs; Ritesh Parajuli; Rita S Mehta; Meihao Wang; Min-Ying Su
Journal:  Front Oncol       Date:  2021-11-17       Impact factor: 6.244

5.  NiftySim: A GPU-based nonlinear finite element package for simulation of soft tissue biomechanics.

Authors:  Stian F Johnsen; Zeike A Taylor; Matthew J Clarkson; John Hipwell; Marc Modat; Bjoern Eiben; Lianghao Han; Yipeng Hu; Thomy Mertzanidou; David J Hawkes; Sebastien Ourselin
Journal:  Int J Comput Assist Radiol Surg       Date:  2014-09-21       Impact factor: 2.924

6.  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

7.  Multiscale Mechano-Biological Finite Element Modelling of Oncoplastic Breast Surgery-Numerical Study towards Surgical Planning and Cosmetic Outcome Prediction.

Authors:  Vasileios Vavourakis; Bjoern Eiben; John H Hipwell; Norman R Williams; Mo Keshtgar; David J Hawkes
Journal:  PLoS One       Date:  2016-07-28       Impact factor: 3.240

8.  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
  8 in total

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