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TitleAuthorYearJournal/ProceedingsReftypeExport
Multi-scale fracture, model reduction, CAD and image as a model

Bordas, S., Kerfriden, P., Beex, L., Atroshchenko, E. and Miller, K. 2015 “Advanced Problems in Mechanics” The International Conference   inproceedings [BibTeX]
BibTeX: 
@inproceedings{2015bordasmillermulti,
  author = {Bordas, Stéphane and Kerfriden, Pierre and Beex, Lars and Atroshchenko, Elena and Miller, Karol},
  title = {Multi-scale fracture, model reduction, CAD and image as a model},
  booktitle = {“Advanced Problems in Mechanics” The International Conference},
  year = {2015}
}
Patient-Specific Meshless Model for Whole-Body Image Registration

[Abstract]

Li, M., Miller, K., Joldes, G., Kikinis, R. and Wittek, A. 2014 Biomedical Simulation   article [BibTeX]
Abstract: Non-rigid registration algorithms that align source and target images play an important role in image-guided surgery and diagnosis. For problems involving large differences between images, such as registration of whole-body radiographic images, biomechanical models have been proposed in recent years. Biomechanical registration has been dominated by Finite Element Method (FEM). In practice, major drawback of FEM is a long time required to generate patient-specific finite element meshes and divide (segment) the image into non-overlapping constituents with different material properties. We eliminate time-consuming mesh generation through application of Meshless Total Lagrangian Explicit Dynamics (MTLED) algorithm that utilises a computational grid in a form of cloud of points. To eliminate the need for segmentation, we use fuzzy tissue classification algorithm to assign the material properties to meshless grid. Comparison of the organ contours in the registered (i.e. source image warped using deformations predicted by our patient-specific meshless model) and target images indicate that our meshless approach facilitates accurate registration of whole-body images with local misalignments of up to only two voxels.
BibTeX: 
@article{2014janliwittekBSpatient,
  author = {Li, Mao and Miller, Karol and Joldes, Grand and Kikinis, Ron and Wittek, Adam},
  title = {Patient-Specific Meshless Model for Whole-Body Image Registration},
  journal = {Biomedical Simulation},
  publisher = {Springer},
  year = {2014},
  url = {https://dx.doi.org/10.1007/978-3-319-12057-7_6},
  doi = {https://doi.org/10.1007/978-3-319-12057-7_6}
}
Beyond finite element method: towards robust and accurate meshless method for computational biomechanics for Medicine

Miller, K. 2014
Vol. 1 ICCM2014, pp. Plenary-Lecture   		inproceedings [BibTeX]
BibTeX: 
@inproceedings{2014millermillerfinite,
  author = {Miller, K.},
  title = {Beyond finite element method: towards robust and accurate meshless method for computational biomechanics for Medicine},
  booktitle = {ICCM2014},
  year = {2014},
  volume = {1},
  pages = {Plenary--Lecture}
}
Objective Evaluation of Accuracy of Intra-Operative Neuroimage Registration

[Abstract]

Garlapati, R.R., Joldes, G.R., Wittek, A., Lam, J., Weisenfeld, N., Hans, A., Warfield, S.K., Kikinis, R. and Miller, K. 2013 Computational Biomechanics for Medicine   bookchapter [BibTeX]
Abstract: Pre-operative brain images that are registered onto relevant intra-operative images can enhance navigation during image-guided neurosurgery. One of the crucial steps in the process of image registration is assessment of its accuracy. The accuracy of an image registration procedure was evaluated in one of our previous studies, for five cases of neurosurgery, using a manual segmentation-based method that is subjective and prone to human errors. The aim of this study is to develop an evaluation method that is objective and automatic. An edge-based Hausdorff Distance (HD) metric based on Canny edges was developed for evaluation. Subsequently, the accuracy of non-rigid registration (NRR) results was evaluated using intra-operative images as ground truth and compared with those from the previous study. The obtained results compared well despite the differences in the methods employed. The edge-based HD metric provides an objective measure for image registration accuracy evaluation.
BibTeX: 
@bookchapter{2013jangarlapatimillerobjective,
  author = {Garlapati, Revanth Reddy and Joldes, Grand Roman and Wittek, Adam and Lam, Jonathan and Weisenfeld, Neil and Hans, Arne and Warfield, Simon K. and Kikinis, Ron and Miller, Karol},
  title = {Objective Evaluation of Accuracy of Intra-Operative Neuroimage Registration},
  booktitle = {Computational Biomechanics for Medicine},
  publisher = {Springer},
  year = {2013},
  url = {https://dx.doi.org/10.1007/978-1-4614-6351-1_9},
  doi = {https://doi.org/10.1007/978-1-4614-6351-1_9}
}
A mobility assignment with industry relevance

[Abstract]

Guzzomi, A.L. and Miller, K. 2013 New Trends in Mechanism and Machine Science   bookchapter [BibTeX]
Abstract: In an attempt to improve the way students prepare for industry a 3rd year mechanisms and multibody systems class was given an assignment with a non-traditional scope and marking guide. Although the team based assignment, like those of prior years, involved mobility analysis of real historical systems in the form of a formal report, it was proposed that the assignment be marked to industry expectations. This meant 100% if the conclusions were satisfactory and 0% if they were not. This experience produced many interesting outcomes and these are discussed. The paper describes the process that led to the implementation of this new assignment structure. The methodology used in its development and reflections of both the authors and the students are discussed.
BibTeX: 
@bookchapter{2013janguzzomimillermobility,
  author = {Guzzomi, A. L. and Miller, K.},
  title = {A mobility assignment with industry relevance},
  booktitle = {New Trends in Mechanism and Machine Science},
  publisher = {Springer},
  year = {2013},
  url = {https://dx.doi.org/10.1007/978-94-007-4902-3_74},
  doi = {https://doi.org/10.1007/978-94-007-4902-3_74}
}
3D Algorithm for Simulation of Soft Tissue Cutting

[Abstract]

Jin, X., Joldes, G.R., Miller, K. and Wittek, A. 2013 Computational Biomechanics for Medicine   bookchapter [BibTeX]
Abstract: Modelling and simulation of soft tissue cutting in 3D remain one of the most challenging problems in surgery simulation, not only because of the nonlinear geometric and material behaviour exhibited by soft tissue but also due to the complexity of introducing the cutting-induced discontinuity. In most publications, the progressive surgical cutting is modelled by conventional finite element (FE) method, in which the high computational cost and error accumulation due to re-meshing constrain the computational efficiency and accuracy. In this paper, a meshless Total Lagrangian Adaptive Dynamic Relaxation (MTLADR) 3D cutting algorithm is proposed to predict the steady-state responses of soft tissue at any stage of surgical cutting in 3D. The MTLADR 3D algorithm features a spatial discretisation using a cloud of nodes. With the benefits of no meshing and no re-meshing, the cutting-induced discontinuity is modelled and simulated by adding nodes on the cutting faces and implementing the visibility criterion with the aid of the level set method. The accuracy of the MTLADR 3D cutting algorithm is verified against the established nonlinear solution procedures available in commercial FE software Abaqus.
BibTeX: 
@bookchapter{2013janjinwittek3d,
  author = {Jin, Xia and Joldes, Grand Roman and Miller, Karol and Wittek, Adam},
  title = {3D Algorithm for Simulation of Soft Tissue Cutting},
  booktitle = {Computational Biomechanics for Medicine},
  publisher = {Springer},
  year = {2013},
  url = {https://dx.doi.org/10.1007/978-1-4614-6351-1_6},
  doi = {https://doi.org/10.1007/978-1-4614-6351-1_6}
}
Intra-operative Update of Neuro-images: Comparison of Performance of Image Warping Using Patient-Specific Biomechanical Model and BSpline Image Registration

[Abstract]

Mostayed, A., Garlapati, R.R., Joldes, G.R., Wittek, A., Kikinis, R., Warfield, S.K. and Miller, K. 2013 Computational Biomechanics for Medicine   bookchapter [BibTeX]
Abstract: This paper compares the warping of neuro-images using brain deformation predicted by means of patient-specific biomechanical model with the neuro-image registration using BSpline-based free form deformation algorithm. Deformation fields obtained from both algorithms are qualitatively compared and overlaps of edges extracted from the images are examined. Finally, an edge-based Hausdorff distance metric is defined to quantitatively evaluate the accuracy of registration for these two algorithms. From the results it is concluded that the patient-specific biomechanical model ensures higher registration accuracy than the BSpline registration algorithm.
BibTeX: 
@bookchapter{2013janmostayedmillerintra,
  author = {Mostayed, Ahmed and Garlapati, Revanth Reddy and Joldes, Grand Roman and Wittek, Adam and Kikinis, Ron and Warfield, Simon K. and Miller, Karol},
  title = {Intra-operative Update of Neuro-images: Comparison of Performance of Image Warping Using Patient-Specific Biomechanical Model and BSpline Image Registration},
  booktitle = {Computational Biomechanics for Medicine},
  publisher = {Springer},
  year = {2013},
  url = {https://dx.doi.org/10.1007/978-1-4614-6351-1_12},
  doi = {https://doi.org/10.1007/978-1-4614-6351-1_12}
}
Performing Brain Image Warping Using the Deformation Field Predicted by a Biomechanical Model

[Abstract]

Joldes, G.R., Wittek, A., Warfield, S.K. and Miller, K. 2012 Computational Biomechanics for Medicine   bookchapter [BibTeX]
Abstract: Biomechanical modeling has become a viable alternative to purely image-based approaches for predicting brain deformation during surgery. Most of the time, a finite element mesh is used for computing the deformation field. Although many papers discuss methods for obtaining the deformation field, there is little information on how it will be used, especially for updating images intraoperatively. In this paper, we discuss some requirements related to the use of this deformation field for warping high quality preoperative brain images. A software implementation is presented, which satisfies most of these requirements. Based on this implementation, we outline some of the difficulties in performing brain registration intraoperatively in real time and propose possible solutions.
BibTeX: 
@bookchapter{2012janjoldesmillerCBfMperforming,
  author = {Joldes, Grand Roman and Wittek, Adam and Warfield, Simon K. and Miller, Karol},
  title = {Performing Brain Image Warping Using the Deformation Field Predicted by a Biomechanical Model},
  journal = {Computational Biomechanics for Medicine},
  publisher = {Springer},
  year = {2012},
  url = {https://dx.doi.org/10.1007/978-1-4614-3172-5_10},
  doi = {https://doi.org/10.1007/978-1-4614-3172-5_10}
}
Modeling Heterogeneous Tumor Growth Using Hybrid Cellular Automata

[Abstract]

Shrestha, S.M.B., Joldes, G., Wittek, A. and Miller, K. 2012 Computational Biomechanics for Medicine   bookchapter [BibTeX]
Abstract: We show that heterogeneity of cells that compose a tumor leads to its irregular growth. We model avascular tumor growth using cellular automata (CA). In our model, we take into account the composition of cells and intercellular adhesion in addition to processes involved in cell cycle—proliferation, quiescence, apoptosis and necrosis. More importantly, we consider cell mutation that gives rise to a different phenotype and therefore, a tumor with heterogeneous population of cells. A new phenotype is probabilistically chosen and has the ability to survive at lower levels of nutrient concentration and reproduce faster. We solve diffusion equation using central difference method to determine the concentration of nutrients, in particular, oxygen available to each cell during the growth process. We present the growth simulation and demonstrate similarity with theoretical findings.
BibTeX: 
@bookchapter{2012janshresthamillerCBfMmodeling,
  author = {Shrestha, Sachin Man Bajimaya and Joldes, Grand and Wittek, Adam and Miller, Karol},
  title = {Modeling Heterogeneous Tumor Growth Using Hybrid Cellular Automata},
  journal = {Computational Biomechanics for Medicine},
  publisher = {Springer},
  year = {2012},
  url = {https://dx.doi.org/10.1007/978-1-4614-3172-5_14},
  doi = {https://doi.org/10.1007/978-1-4614-3172-5_14}
}
Neuroimage as a Biomechanical Model: Toward New Computational Biomechanics of the Brain

[Abstract]

Zhang, J.Y., Joldes, G.R., Wittek, A., Horton, A., Warfield, S.K. and Miller, K. 2012 Computational Biomechanics for Medicine   bookchapter [BibTeX]
Abstract: In recent years, predicting brain deformations during surgery using methods of computational biomechanics has become a viable alternative to purely image-based techniques. However, the difficulties with patient-specific computational grid generation prevent the widespread application of biomechanical modeling in medicine. For more efficient computational grid generation, we propose a statistical meshless model based on fuzzy tissue classification and mechanical property assignment, and meshless (i.e., based on the unstructured cloud of points that do not form elements) solution method. Instead of hard segmentation that divides intracranial area into nonoverlapping, constituent regions we use statistical classification to get the fuzzy membership functions of tissue classes for each voxel. Material properties are assigned to integration points based on this soft classification. Verification example shows that the proposed model gives equivalent results—difference in computed brain deformations of at most 0.2 mm—to the finite element method (FEM) and can certainly be considered for use in future simulations. Based on this concept, patient-specific computational models can be more efficiently and robustly generated in the clinical workflow.
BibTeX: 
@bookchapter{2012janzhangmillerCBfMneuroimage,
  author = {Zhang, Johnny Y. and Joldes, Grand Roman and Wittek, Adam and Horton, Ashley and Warfield, Simon K. and Miller, Karol},
  title = {Neuroimage as a Biomechanical Model: Toward New Computational Biomechanics of the Brain},
  journal = {Computational Biomechanics for Medicine},
  publisher = {Springer},
  year = {2012},
  url = {https://dx.doi.org/10.1007/978-1-4614-3172-5_4},
  doi = {https://doi.org/10.1007/978-1-4614-3172-5_4}
}
TOWARDS DETERMINING MECHANICAL PROPERTIES OF THE BRAIN-SKULL INTERFACE: A STUDY USING BRAIN INDENTATION EXPERIMENT AND MODELLING

M. Mazumder A. Wittek, A.M.G.J.R.H. and Miller, K. 2012 Proceedings of10th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering., pp. 942-947   inproceedings [BibTeX]
BibTeX: 
@inproceedings{2012m.mazumdermillertowards,
  author = {M. Mazumder, A. Wittek, A. Mostayed, G.R. Joldes, R. Hart and K. Miller},
  title = {TOWARDS DETERMINING MECHANICAL PROPERTIES OF THE BRAIN-SKULL INTERFACE: A STUDY USING BRAIN INDENTATION EXPERIMENT AND MODELLING},
  booktitle = {Proceedings of10th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering.},
  year = {2012},
  pages = {942--947}
}
2-D MESHLESS ALGORITHM FOR MODELLING OF SOFT TISSUE UNDERGOING FRAGMENTATION AND LARGE DEFORMATION: VERIFICATION AND PERFORMANCE EVALUATION

Xia Jin Guiyong Zhang, G.R.J.K.H.A.W. 2012 Proceedings of10th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering., pp. 327-332   inproceedings [BibTeX]
BibTeX: 
@inproceedings{2012xiajinxiajin2,
  author = {Xia Jin, Guiyong Zhang, Grand. R. Joldes, King. H, Adam Wittek},
  title = {2-D MESHLESS ALGORITHM FOR MODELLING OF SOFT TISSUE UNDERGOING FRAGMENTATION AND LARGE DEFORMATION: VERIFICATION AND PERFORMANCE EVALUATION},
  booktitle = {Proceedings of10th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering.},
  year = {2012},
  pages = {327--332}
}
Real-Time Nonlinear Finite Element Computations on GPU: Handling of Different Element Types

[Abstract]

Joldes, G.R., Wittek, A. and Miller, K. 2011 Computational Biomechanics for Medicine   bookchapter [BibTeX]
Abstract: Application of biomechanical modeling techniques in the area of medical image analysis and surgical simulation implies two conflicting requirements: accurate results and high solution speeds. Accurate results can be obtained only by using appropriate models and solution algorithms. In our previous papers, we have presented algorithms and solution methods for performing accurate nonlinear finite element analysis of brain shift (which includes mixed mesh, different nonlinear material models, finite deformations and brain–skull contacts) in less than 5 s on a personal computer using a Graphics Processing Unit (GPU) for models having up to 50,000 degrees of freedom. In this chapter, we compare several approaches for implementing different element types on the GPU using the NVIDIA Compute Unified Device Architecture. Our results can be used as a guideline for selecting the best GPU implementation approach for finite element algorithms which require mixed meshes or even for meshless methods.
BibTeX: 
@bookchapter{2011janjoldesmillerCBfMreal,
  author = {Joldes, Grand R. and Wittek, Adam and Miller, Karol},
  title = {Real-Time Nonlinear Finite Element Computations on GPU: Handling of Different Element Types},
  journal = {Computational Biomechanics for Medicine},
  publisher = {Springer},
  year = {2011},
  url = {https://dx.doi.org/10.1007/978-1-4419-9619-0_8},
  doi = {https://doi.org/10.1007/978-1-4419-9619-0_8}
}
On the Effects of Model Complexity in Computing Brain Deformation for Image-Guided Neurosurgery

[Abstract]

Ma, J., Wittek, A., Zwick, B., Joldes, G.R., Warfield, S.K. and Miller, K. 2011 Computational Biomechanics for Medicine   bookchapter [BibTeX]
Abstract: Intra-operative images acquired during brain surgery do not provide sufficient detail to confidently locate brain internal structures that have been identified in high-resolution pre-operative images. However, the pre-operative images can be warped to the intra-operative position of brain using predicted deformation field. While craniotomy-induced brain shift deformation can be accurately computed using patient-specific finite element models in real-time, accurate segmentation and meshing of brain internal structures remains a time-consuming task. In this chapter, we conduct a parametric study to evaluate the sensitivity of the predicted brain shift deformation to model complexity, which includes the effects of disregarding the differences in properties between the parenchyma, tumour and ventricles and applying different approaches for representing the ventricles (as a very soft solid or cavity) to minimise segmentation and meshing effort for model generation. The results suggest that the difference in brain shift deformation predicted by models due to such variation is not significant. Segmentation of brain parenchyma and skull seems sufficient to build models that can accurately predict craniotomy-induced brain shift deformation.
BibTeX: 
@bookchapter{2011janmamillerCBfMeffects,
  author = {Ma, Jiajie and Wittek, Adam and Zwick, Benjamin and Joldes, Grand R. and Warfield, Simon K. and Miller, Karol},
  title = {On the Effects of Model Complexity in Computing Brain Deformation for Image-Guided Neurosurgery},
  journal = {Computational Biomechanics for Medicine},
  publisher = {Springer},
  year = {2011},
  url = {https://dx.doi.org/10.1007/978-1-4419-9619-0_6},
  doi = {https://doi.org/10.1007/978-1-4419-9619-0_6}
}
The Effects of Young’s Modulus on Predicting Prostate Deformation for MRI-Guided Interventions

[Abstract]

McAnearney, S., Fedorov, A., Joldes, G.R., Hata, N., Tempany, C., Miller, K. and Wittek, A. 2011 Computational Biomechanics for Medicine   bookchapter [BibTeX]
Abstract: Accuracy of image-guided prostate interventions can be improved by warping (i.e., nonrigid registration) of high-quality multimodal preoperative magnetic resonance images to the intraoperative prostate geometry. Patient-specific biomechanical models have been applied in several studies when predicting the prostate intraoperative deformations for such warping. Obtaining exact patient-specific information about the stress parameter (e.g., Young’s modulus) of the prostate peripheral zone (PZ) and central gland (CG) for such models remains an unsolved problem. In this study, we investigated the effects of ratio of Young’s modulus of the central gland ECG to the peripheral zone EPZ when predicting the prostate intraoperative deformation for ten cases of prostate brachytherapy. The patient-specific prostate models were implemented by means of the specialized nonlinear finite element procedures that utilize total Lagrangian formulation and explicit integration in time domain. The loading was defined by prescribing deformations on the prostate outer surface. The neo-Hookean hyperelastic constitutive model was applied to simulate the PZ and CG mechanical responses. The PZ to CG Young’s modulus ratio ECG:EPZ was varied between 1:1 (upper bound of the literature data) and 1:40 (lower bound of the literature data). The study indicates that the predicted prostate intraoperative deformations and results of the prostate MRIs nonrigid registration obtained using the predicted deformations depend very weakly on the ECG:EPZ ratio.
BibTeX: 
@bookchapter{2011janmcanearneywittekCBfMeffects,
  author = {McAnearney, Stephen and Fedorov, Andriy and Joldes, Grand R. and Hata, Nobuhiko and Tempany, Clare and Miller, Karol and Wittek, Adam},
  title = {The Effects of Young’s Modulus on Predicting Prostate Deformation for MRI-Guided Interventions},
  journal = {Computational Biomechanics for Medicine},
  publisher = {Springer},
  year = {2011},
  url = {https://dx.doi.org/10.1007/978-1-4419-9619-0_5},
  doi = {https://doi.org/10.1007/978-1-4419-9619-0_5}
}
Biomechanical Modeling of the Brain for Computer-Assisted Neurosurgery

[Abstract]

Miller, K., Wittek, A. and Joldes, G. 2011 Biomechanics of the Brain   bookchapter [BibTeX]
Abstract: During neurosurgery, the brain significantly deforms. Despite the enormous complexity of the brain (see Chap. 2) many aspects of its response can be reasonably described in purely mechanical terms, such as displacements, strains and stresses. They can therefore be analyzed using established methods of continuum mechanics. In this chapter, we discuss approaches to biomechanical modeling of the brain from the perspective of two distinct applications: neurosurgical simulation and neuroimage registration in image-guided surgery. These two challenging applications are described below.1
BibTeX: 
@bookchapter{2011janmillerjoldesBotBbiomechanical,
  author = {Miller, K. and Wittek, A. and Joldes, G.},
  title = {Biomechanical Modeling of the Brain for Computer-Assisted Neurosurgery},
  journal = {Biomechanics of the Brain},
  publisher = {Springer},
  year = {2011},
  url = {https://dx.doi.org/10.1007/978-1-4419-9997-9_6},
  doi = {https://doi.org/10.1007/978-1-4419-9997-9_6}
}
Introduction

[Abstract]

Miller, K. 2011 Biomechanics of the Brain   bookchapter [BibTeX]
Abstract: The mechanical properties of living tissues continue to be the major topic of ­biomechanical investigations. Over the years, a vast amount of knowledge about load-bearing tissues, such as bones, ligaments, muscles and other components of the musculoskeletal system, blood vessels (and blood), lungs, skin and hair, has been published in journals and books. The very soft tissues of organs whose role has little or nothing to do with transmitting mechanical loads had been, until recently, outside the scope of the mainstream biomechanical research. Extremely important organs such as the liver, kidneys, prostate and other abdominal organs, and ­especially the brain, had been largely neglected by biomechanics.
BibTeX: 
@bookchapter{2011janmillermillerBotBintroduction,
  author = {Miller, Karol},
  title = {Introduction},
  journal = {Biomechanics of the Brain},
  publisher = {Springer},
  year = {2011},
  url = {https://dx.doi.org/10.1007/978-1-4419-9997-9_1},
  doi = {https://doi.org/10.1007/978-1-4419-9997-9_1}
}
Computational Biomechanics of the Brain; Application to Neuroimage Registration

[Abstract]

Miller, K., Wittek, A., Joldes, G., Ma, J. and Zwick, B.J. 2011 Neural Tissue Biomechanics   article [BibTeX]
Abstract: We present selected topics in the area of mathematical and numerical modelling of the brain biomechanics for brain image registration. We show how to describe registration in purely mechanical terms, such as displacements, strains and stresses and perform it using established methods of continuum mechanics. We advocate the use of fully non-linear theory of continuum mechanics. We discuss in some detail modelling geometry, boundary conditions, loading and material properties. We consider numerical problems such as the use of hexahedral and mixed hexahedral-tetrahedral meshes as well as meshless spatial discretisation schemes as well as the effects of model complexity on accuracy of brain deformation computation. We advocate the use of Total Lagrangian Formulation of both finite element and meshless methods together with explicit time-stepping procedures. We support our recommendations and conclusions with an example of the computation of the brain shift for intra-operative image registration.
BibTeX: 
@article{2011janmillerzwickNTBcomputational,
  author = {Miller, Karol and Wittek, Adam and Joldes, Grand and Ma, Jiajie and Zwick, Ben Jamin},
  title = {Computational Biomechanics of the Brain; Application to Neuroimage Registration},
  journal = {Neural Tissue Biomechanics},
  publisher = {Springer},
  year = {2011},
  url = {https://dx.doi.org/10.1007/8415_2011_80},
  doi = {https://doi.org/10.1007/8415_2011_80}
}
Total Lagrangian Explicit Dynamics-Based Simulation of Tissue Tearing

[Abstract]

Vemaganti, K., Joldes, G.R., Miller, K. and Wittek, A. 2011 Computational Biomechanics for Medicine   bookchapter [BibTeX]
Abstract: This study presents an approach to modeling the tearing of tissue in two dimensions taking into account both material and geometrical nonlinearities. The approach is based on the total Lagrangian explicit dynamics (TLED) algorithm and realigns edges in the mesh along the path of the tear by node relocation. As such, no new elements are created during the propagation of the tear. The material is assumed to be isotropic, and the tearing criterion is based on the maximum node-averaged principal stress. Preliminary results show that the approach is capable of handling both isotropic and anisotropic tears.
BibTeX: 
@bookchapter{2011janvemagantiwittekCBfMtotal,
  author = {Vemaganti, Kumar and Joldes, Grand R. and Miller, Karol and Wittek, Adam},
  title = {Total Lagrangian Explicit Dynamics-Based Simulation of Tissue Tearing},
  journal = {Computational Biomechanics for Medicine},
  publisher = {Springer},
  year = {2011},
  url = {https://dx.doi.org/10.1007/978-1-4419-9619-0_7},
  doi = {https://doi.org/10.1007/978-1-4419-9619-0_7}
}
Algorithms for Computational Biomechanics of the Brain

[Abstract]

Wittek, A., Joldes, G. and Miller, K. 2011 Biomechanics of the Brain   bookchapter [BibTeX]
Abstract: Modeling of the brain responses due to injury-causing transients and surgery is a problem of continuum mechanics that involves irregular geometry, complex loading and boundary conditions, non-linear materials, and large deformations (see Chaps. 5 and 6). Finding a solution for such a problem requires computational algorithms of non-linear continuum mechanics.
BibTeX: 
@bookchapter{2011janwittekmillerBotBalgorithms,
  author = {Wittek, A. and Joldes, G. and Miller, K.},
  title = {Algorithms for Computational Biomechanics of the Brain},
  journal = {Biomechanics of the Brain},
  publisher = {Springer},
  year = {2011},
  url = {https://dx.doi.org/10.1007/978-1-4419-9997-9_9},
  doi = {https://doi.org/10.1007/978-1-4419-9997-9_9}
}
Can Vascular Dynamics Cause Normal Pressure Hydrocephalus?

[Abstract]

Dutta-Roy, T., Wittek, A. and Miller, K. 2010 Computational Biomechanics for Medicine   bookchapter [BibTeX]
Abstract: This study investigated the hypothesis that changes in the brain vasculature system can explain the mechanics of normal pressure hydrocephalus (NPH) growth. A generic 3-D mesh of a healthy human brain was created. We used a fully non-linear (geometric, constitutive and boundary conditions) 3-D model of the brain parenchyma. The brain parenchyma was modelled as a nearly incompressible, single-phase continuum. A hyperelastic constitutive law and finite deformation theory described the deformations within the brain parenchyma. The brain vasculature system was modelled biomechanically by modifying the relaxed shear modulus according to the cardiac cycle to produce a time varying shear modulus. As no study currently exists on the effects of vasculature on brain parenchyma material properties, a parametric investigation was conducted by varying the brain parenchyma relaxed shear modulus. It is widely believed that no more than 1 mm of Hg (133.416 Pa) transmantle pressure difference is associated with NPH. Hence, we loaded the brain parenchyma with 1 mm of Hg transmantle pressure difference to investigate this suggestion. Fully non-linear, implicit, quasi-static finite element procedures in the time domain were used to obtain the deformation of the brain parenchyma and the ventricles. The results of the simulations showed that 1 mm of Hg (133.416 Pa) did not produce the clinical condition of NPH, even with brain vasculature effects taken into account. We conclude from our work that it is highly unlikely for a phenomenon, such as the brain vasculature effects due to the cardiac cycle, which occurs many times a minute to be able to influence an event such as NPH which presents itself over a time scale of hours to days. We further suggest that the hypothesis of a purely mechanical basis for NPH growth needs to be revised.
BibTeX: 
@bookchapter{2010jandutta-roymillercan,
  author = {Dutta-Roy, Tonmoy and Wittek, Adam and Miller, Karol},
  title = {Can Vascular Dynamics Cause Normal Pressure Hydrocephalus?},
  booktitle = {Computational Biomechanics for Medicine},
  publisher = {Springer},
  year = {2010},
  url = {https://dx.doi.org/10.1007/978-1-4419-5874-7_8},
  doi = {https://doi.org/10.1007/978-1-4419-5874-7_8}
}
Cortical Surface Motion Estimation for Brain Shift Prediction

[Abstract]

Joldes, G.R., Wittek, A. and Miller, K. 2010 Computational Biomechanics for Medicine   bookchapter [BibTeX]
Abstract: In this chapter we present an algorithm for computing the displacement of the exposed surface of the brain during surgery. The motion of the cortical surface is recovered by registering the preoperative surface extracted from high-resolution MRI images to the intraoperative surface acquired during surgery. The recovered motion can then be used for driving a biomechanical model in order to predict the displacement of the internal brain structures, especially the tumor, which can be presented to the surgeon using an image-guided neurosurgery system. Our algorithm combines an image registration method with curvature information associated with the features of the brain surface to perform the non-rigid surface registration. The extracted displacement field can be used directly for driving a biomechanical model, as it does not include any implausible deformations. It also works in cases when the boundaries of the two registered surfaces are not identical, extracting the displacements only for the overlapping regions of the two surfaces. We tested the accuracy of the proposed algorithm using synthetically generated data as well as surfaces extracted from preoperative and intraoperative MRI images of the brain.
BibTeX: 
@bookchapter{2010janjoldesmillercortical,
  author = {Joldes, Grand Roman and Wittek, Adam and Miller, Karol},
  title = {Cortical Surface Motion Estimation for Brain Shift Prediction},
  booktitle = {Computational Biomechanics for Medicine},
  publisher = {Springer},
  year = {2010},
  url = {https://dx.doi.org/10.1007/978-1-4419-5874-7_6},
  doi = {https://doi.org/10.1007/978-1-4419-5874-7_6}
}
Accuracy of Non-linear FE Modelling for Surgical Simulation: Study Using Soft Tissue Phantom

[Abstract]

Ma, J., Wittek, A., Singh, S., Joldes, G.R., Washio, T., Chinzei, K. and Miller, K. 2010 Computational Biomechanics for Medicine   bookchapter [BibTeX]
Abstract: In this chapter, we evaluated the accuracy of non-linear FE modelling in application to surgical simulation. We compared experiment and FE modelling of indentation of the soft tissue phantom. The evaluation was done in terms of soft tissue phantom deformation and the forces acting on the indenter. The soft tissue phantom deformation was measured by tracking 3D motions of X-ray opaque markers placed in the direct neighbourhood under the indenter with a custom-built bi-plane X-ray image intensifiers (XRII) system. The modelling of soft tissue phantom indentation was conducted using the ABAQUS/standard finite element solver. Specific constitutive properties of the soft tissue phantom determined through semi-confined uniaxial compression tests were used in the model. The model accurately predicted the indentation force–displacement relations and marker displacements. The agreement between modelling and experimental results verifies the reliability of our FE modelling techniques and confirms the predictive power of these techniques in surgical simulation.
BibTeX: 
@bookchapter{2010janmamilleraccuracy,
  author = {Ma, Jiajie and Wittek, Adam and Singh, Surya and Joldes, Grand Roman and Washio, Toshikatsu and Chinzei, Kiyoyuki and Miller, Karol},
  title = {Accuracy of Non-linear FE Modelling for Surgical Simulation: Study Using Soft Tissue Phantom},
  booktitle = {Computational Biomechanics for Medicine},
  publisher = {Springer},
  year = {2010},
  url = {https://dx.doi.org/10.1007/978-1-4419-5874-7_4},
  doi = {https://doi.org/10.1007/978-1-4419-5874-7_4}
}
Evaluation of accuracy of non-linear finite element computations for surgical simulation: study using brain phantom

Ma, J., Wittek, A., Singh, S., Joldes, G., Washio, T., Chinzei, K. and Miller, K. 2010 Computer methods in biomechanics and biomedical engineering
Vol. 13 (6) , pp. 783-794   		article [BibTeX]
BibTeX: 
@article{2010mamillerCmibabeevaluation,
  author = {Ma, J and Wittek, A and Singh, S and Joldes, G and Washio, T and Chinzei, K and Miller, K},
  title = {Evaluation of accuracy of non-linear finite element computations for surgical simulation: study using brain phantom},
  journal = {Computer methods in biomechanics and biomedical engineering},
  publisher = {Taylor & Francis Group},
  year = {2010},
  volume = {13},
  number = {6},
  pages = {783--794},
  doi = {https://doi.org/10.1080/10255841003628995}
}
Subject-specific non-linear biomechanical model of needle insertion into brain

Wittek, A., Dutta-Roy, T., Taylor, Z., Horton, A., Washio, T., Chinzei, K. and Miller, K. 2008 Computer methods in biomechanics and biomedical engineering
Vol. 11 (2) , pp. 135-146   		article [BibTeX]
BibTeX: 
@article{2008wittekmillerCmibabesubject,
  author = {Wittek, A and Dutta-Roy, T and Taylor, Z and Horton, A and Washio, T and Chinzei, K and Miller, K},
  title = {Subject-specific non-linear biomechanical model of needle insertion into brain},
  journal = {Computer methods in biomechanics and biomedical engineering},
  publisher = {Taylor & Francis Group},
  year = {2008},
  volume = {11},
  number = {2},
  pages = {135--146},
  doi = {https://doi.org/10.1080/10255840701688095}
}
Computer simulation of brain shift using an Element Free Galerkin method

Horton, A., Wittek, A. and Miller, K. 2007 Proceedings of 7th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering, pp. 906-911   inproceedings [BibTeX]
BibTeX: 
@inproceedings{2007hortonmillercomputer,
  author = {Horton, A. and Wittek, A. and Miller, K.},
  title = {Computer simulation of brain shift using an Element Free Galerkin method},
  booktitle = {Proceedings of 7th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering},
  year = {2007},
  pages = {906--911}
}
Towards non-linear finite element computations in real time

Joldes, G., Wittek, A. and Miller, K. 2007 Proceedings of 7th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering, pp. 894-899   inproceedings [BibTeX]
BibTeX: 
@inproceedings{2007joldesmillertowards,
  author = {Joldes, G. and Wittek, A. and Miller, K.},
  title = {Towards non-linear finite element computations in real time},
  booktitle = {Proceedings of 7th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering},
  year = {2007},
  pages = {894--899}
}
Linear versus non-linear computation of the brain shift

Miller, K., Hawkins, T. and Wittek, A. 2007 Proceedings of 7th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering, pp. 888-893   inproceedings [BibTeX]
BibTeX: 
@inproceedings{2007millerwitteklinear,
  author = {Miller, K. and Hawkins, T. and Wittek, A.},
  title = {Linear versus non-linear computation of the brain shift},
  booktitle = {Proceedings of 7th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering},
  year = {2007},
  pages = {888--893}
}
Confocal arthroscopy-based patient-specific constitutive models of cartilaginous tissues - II: prediction of reaction force history of meniscal cartilage specimens.

[Abstract]

Taylor, Z.A., Kirk, T.B. and Miller, K. 2007 Computer methods in biomechanics and biomedical engineering
Vol. 10 (5) , pp. 327-336   		article [BibTeX]
Abstract: The theoretical framework developed in a companion paper (Part I) is used to derive estimates of mechanical response of two meniscal cartilage specimens. The previously developed framework consisted of a constitutive model capable of incorporating confocal image-derived tissue microstructural data. In the present paper (Part II) fibre and matrix constitutive parameters are first estimated from mechanical testing of a batch of specimens similar to, but independent from those under consideration. Image analysis techniques which allow estimation of tissue microstructural parameters form confocal images are presented. The constitutive model and image-derived structural parameters are then used to predict the reaction force history of the two meniscal specimens subjected to partially confined compression. The predictions are made on the basis of the specimens' individual structural condition as assessed by confocal microscopy and involve no tuning of material parameters. Although the model does not reproduce all features of the experimental curves, as an unfitted estimate of mechanical response the prediction is quite accurate. In light of the obtained results it is judged that more general non-invasive estimation of tissue mechanical properties is possible using the developed framework.
BibTeX: 
@article{2007octtaylormillerCMBBEconfocal,
  author = {Taylor, Zeike A and Kirk, Thomas B and Miller, Karol},
  title = {Confocal arthroscopy-based patient-specific constitutive models of cartilaginous tissues - II: prediction of reaction force history of meniscal cartilage specimens.},
  journal = {Computer methods in biomechanics and biomedical engineering},
  school = {Intelligent Systems for Medicine Laboratory, School of Mechanical Engineering, The University of Western Australia, Perth, WA, Australia.},
  year = {2007},
  volume = {10},
  number = {5},
  pages = {327--336},
  url = {https://dx.doi.org/10.1080/10255840701336828},
  doi = {https://doi.org/10.1080/10255840701336828}
}
Towards Realistic Surgical Simulation: Biomechanics of Needle Insertion into the Brain

[Abstract]

Dutta-Roy, T., Wittek, A., Taylor, Z., Chinzei, K., Washio, T. and Miller, K. 2006 Romansy 16   inproceedings [BibTeX]
Abstract: Robotic surgery has been recognised in the past few years to have immense potential. Understanding the biomechanics of surgical procedures is central to robotic surgery. Needle insertion into soft tissues is a common surgical procedure but the biomechanics of needle insertion is poorly understood. We developed a computational biomechanical model to understand the mechanics of needle insertion into the brain tissue. The brain tissue is considered as a single phase continuum undergoing finite deformations. A non-linear constitutive model of the brain tissue is used. Precise geometrical model of the brain is obtained from MRI images and the brain mesh is created. The brain computational model is verified by comparing with previously published experimental results for porcine brain indentation. The reaction forces acting on the needle during insertion are obtained using fully non-linear, explicit Finite Element procedures in time domain.
BibTeX: 
@inproceedings{2006jandutta-roymillerR1towards,
  author = {Dutta-Roy, Tonmoy and Wittek, Adam and Taylor, Zeike and Chinzei, Kiyoyuki and Washio, Toshikatsu and Miller, Karol},
  title = {Towards Realistic Surgical Simulation: Biomechanics of Needle Insertion into the Brain},
  booktitle = {Romansy 16},
  publisher = {Springer},
  year = {2006},
  url = {https://dx.doi.org/10.1007/3-211-38927-X_38},
  doi = {https://doi.org/10.1007/3-211-38927-X_38}
}
Development of confocal image-based patient-specific models of cartilaginous tissues

Taylor, Z., Kirk, T. and Miller, K. 2006 Proceedings of 7th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering, pp. 846-851   inproceedings [BibTeX]
BibTeX: 
@inproceedings{2006taylormillerdevelopment,
  author = {Taylor, ZA and Kirk, TB and Miller, K},
  title = {Development of confocal image-based patient-specific models of cartilaginous tissues},
  booktitle = {Proceedings of 7th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering},
  year = {2006},
  pages = {846--851}
}
Modeling of Brain Mechanical Properties for Computer-Integrated Medicine

[Abstract]

Miller, K. and Nowinski, W.L. 2005 Robotics Research. The Eleventh International Symposium   bookchapter [BibTeX]
Abstract: Many modern applications of technology to medicine, such as robotic surgery, non-rigid registration, virtual reality operation planning and surgeon training systems, and surgical simulators, require knowledge of mechanical properties of very soft tissues. In this paper we describe and identify a model of mechanical properties of brain tissue aimed in particular at integration with interactive brain atlases. A non-linear, viscoelastic model based on the generalization of the Ogden strain energy hyperelastic constitutive equation is proposed. The material parameters are identified using in-vivo experimental results. The model accounts well for brain tissue deformation behavior in both tension and compression (natural strain ε〈 − 0.3, 0.2〉 ) for strain rates typical for surgical procedures. It can be immediately applied in large-scale finite element simulations and, therefore, offers the possibility of incorporating mechanics into surgical planning and training systems such as NeuroPlanner and BrainBench. Finally we show that the brain model identified based on in-vivo experiments can be applied in the more realistic in-vivo setting.
BibTeX: 
@bookchapter{2005janmillernowinskiRRTEISmodeling,
  author = {Miller, Karol and Nowinski, Wieslaw L.},
  title = {Modeling of Brain Mechanical Properties for Computer-Integrated Medicine},
  journal = {Robotics Research. The Eleventh International Symposium},
  publisher = {Springer},
  year = {2005},
  url = {https://dx.doi.org/10.1007/11008941_14},
  doi = {https://doi.org/10.1007/11008941_14}
}
DEVELOPMENT OF A CONFOCAL ARTHROSCOPE FOR NON-INVASIVE HISTOLOGICAL ASSESSMENT OF CARTILAGE

Zheng, M., Willers, C., Wood, D., Jones, C., Smolinski, D., Wu, J., Miller, K. and Kirk, T. 2005 Journal of Bone & Joint Surgery, British Volume
Vol. 87 (SUPP III) , pp. 347-347   		article [BibTeX]
BibTeX: 
@article{2005zhengkirkJoBJSBVdevelopment,
  author = {Zheng, MH and Willers, C and Wood, DJ and Jones, CW and Smolinski, D and Wu, JP and Miller, K and Kirk, TB},
  title = {DEVELOPMENT OF A CONFOCAL ARTHROSCOPE FOR NON-INVASIVE HISTOLOGICAL ASSESSMENT OF CARTILAGE},
  journal = {Journal of Bone & Joint Surgery, British Volume},
  publisher = {British Editorial Society of Bone and Joint Surgery},
  year = {2005},
  volume = {87},
  number = {SUPP III},
  pages = {347--347}
}
Biomechanics without mechanics: calculating soft tissue deformation without differential equations of equilibrium

Miller, K. 2004 Computer Methods in Biomechanics and Biomedical Engineering Conference, pp. 1-8   inproceedings [BibTeX]
BibTeX: 
@inproceedings{2004millermillerbiomechanics,
  author = {Miller, K.},
  title = {Biomechanics without mechanics: calculating soft tissue deformation without differential equations of equilibrium},
  booktitle = {Computer Methods in Biomechanics and Biomedical Engineering Conference},
  year = {2004},
  pages = {1--8}
}
Design and Applications of Parallel Robots

[Abstract]

Miller, K. 2003 Robotics Research   bookchapter [BibTeX]
Abstract: An optimal kinematic design method suited for parallel manipulators is described. The optimal configuration for a Delta-type three-degree-of-freedom spatial, translational manipulator, known as the New University of Western Australia Robot (NUWAR) is presented, and shown to be advantageous over the Delta configuration in terms of workspace volume. These results led to the construction of a prototype and an Australian Patent application.The kinematic optimisation process yielding a design, which delivers the best compromise between manipulability and a new performance index: space utilisation, is presented. The process leading to finding an optimal configuration of Linear Delta robot is described.An example medical application of a parallel robot is discussed. The robot is designed to work inside an open magnetic resonance scanner. A concept of a robot control system, based on biomechanical models of organs the robot operates on, is presented.
BibTeX: 
@bookchapter{2003janmillermillerRRdesign,
  author = {Miller, Karol},
  title = {Design and Applications of Parallel Robots},
  journal = {Robotics Research},
  publisher = {Springer},
  year = {2003},
  url = {https://dx.doi.org/10.1007/3-540-36460-9_11},
  doi = {https://doi.org/10.1007/3-540-36460-9_11}
}
Biomechanics of brain for computer assisted surgery

Miller, K. 2003 Zeszyty Naukowe Katedry Mechaniki Stosowanej/Politechnika ląska (20) , pp. 309-314   article [BibTeX]
BibTeX: 
@article{2003millermillerZNKMSbiomechanics,
  author = {Miller, K},
  title = {Biomechanics of brain for computer assisted surgery},
  journal = {Zeszyty Naukowe Katedry Mechaniki Stosowanej/Politechnika ląska},
  year = {2003},
  number = {20},
  pages = {309--314}
}
Microstructural modelling of articular cartilage using 3D confocal endoscopy

Taylor, Z.A., Miller, K. and Kirk, T.B. 2003 International Society of Biomechanics XIXth Congress: the human body in motion, 6-11 July, 2003, Dunedin, New Zealand, pp. 386-386   inproceedings [BibTeX]
BibTeX: 
@inproceedings{2003taylorkirkISoBXCthbim6J2DNZmicrostructural,
  author = {Taylor, Zeike A and Miller, Karol and Kirk, Thomas B},
  title = {Microstructural modelling of articular cartilage using 3D confocal endoscopy},
  booktitle = {International Society of Biomechanics XIXth Congress: the human body in motion, 6-11 July, 2003, Dunedin, New Zealand},
  publisher = {University of Otago},
  year = {2003},
  pages = {386--386}
}
Design of Linear Delta Robot: Compromise Between Manipulability and Workspace Size

[Abstract]

Stock, M. and Miller, K. 2002 Romansy 14   inproceedings [BibTeX]
Abstract: An optimal kinematic design method suited for parallel manipulators is developed. The kinematic optimization process yields a design, which delivers the best compromise between manipulability and a new performance index, space utilization. It is shown that the exhaustive search minimization algorithm is effective for as many as four independent design variables and presents a viable alternative to advanced non-linear programming methods. The manipulability generally exhibits relatively little variation when compared to space utilization. The tendency exists for the solution to converge on a zero workspace size architecture when manipulability is optimized alone. The inclusion of the space utilization index in the cost function is crucial for obtaining realistic design candidates.
BibTeX: 
@inproceedings{2002janstockmillerR1design,
  author = {Stock, Michael and Miller, Karol},
  title = {Design of Linear Delta Robot: Compromise Between Manipulability and Workspace Size},
  booktitle = {Romansy 14},
  publisher = {Springer},
  year = {2002},
  url = {https://dx.doi.org/10.1007/978-3-7091-2552-6_42},
  doi = {https://doi.org/10.1007/978-3-7091-2552-6_42}
}
Mechanics of the New UWA Robot

[Abstract]

Miller, K. 2000 Romansy 13   inproceedings [BibTeX]
Abstract: New University of Western Australia Robot is a variation of the well-known Delta parallel robot. Parallel manipulators possess a number of advantages when compared to traditional serial arms. They offer generally much higher rigidity and smaller mobile mass than their serial counterparts. These features allow much faster and more precise manipulations. The main disadvantage of parallel robots is their small workspace in comparison to serial arms of similar size. Our previous work investigated the influence of motor axes orientation on the workspace volume of Delta type manipulators. This research has shown that the Delta configuration is not optimal and that the configuration characterized by

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BibTeX: 
@inproceedings{2000janmillermillerR1mechanics,
  author = {Miller, Karol},
  title = {Mechanics of the New UWA Robot},
  booktitle = {Romansy 13},
  publisher = {Springer},
  year = {2000},
  url = {https://dx.doi.org/10.1007/978-3-7091-2498-7_6},
  doi = {https://doi.org/10.1007/978-3-7091-2498-7_6}
}
Non-linear computer simulation of brain deformation.

Miller, K. 2000 Biomedical sciences instrumentation
Vol. 37 , pp. 179-184   		article [BibTeX]
BibTeX: 
@article{2000millermillerBsinon,
  author = {Miller, K},
  title = {Non-linear computer simulation of brain deformation.},
  journal = {Biomedical sciences instrumentation},
  year = {2000},
  volume = {37},
  pages = {179--184}
}
New UWA robot--possible application to robotic surgery.

Miller, K. and Chinzei, K. 1999 Biomedical sciences instrumentation
Vol. 36 , pp. 135-140   		article [BibTeX]
BibTeX: 
@article{1999millerchinzeiBsinew,
  author = {Miller, K and Chinzei, K},
  title = {New UWA robot--possible application to robotic surgery.},
  journal = {Biomedical sciences instrumentation},
  year = {1999},
  volume = {36},
  pages = {135--140}
}
Modelling soft tissue using biphasic theory—a word of caution

MILLER, K. 1998 Computer methods in biomechanics and biomedical engineering
Vol. 1 (3) , pp. 261-263   		article [BibTeX]
BibTeX: 
@article{1998millermillerCMIBABMEmodelling,
  author = {MILLER, KAROL},
  title = {Modelling soft tissue using biphasic theory—a word of caution},
  journal = {Computer methods in biomechanics and biomedical engineering},
  publisher = {Taylor & Francis Group},
  year = {1998},
  volume = {1},
  number = {3},
  pages = {261--263},
  doi = {https://doi.org/10.1080/01495739808936706}
}
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