Abstract：
:The ability to predict patient-specific soft tissue deformations is key for computer-integrated surgery systems and the core enabling technology for a new era of personalized medicine. Element-Free Galerkin (EFG) methods are better suited for solving soft tissue deformation problems than the finite element method (FEM) due to their capability of handling large deformation while also eliminating the necessity of creating a complex predefined mesh. Nevertheless, meshless methods based on EFG formulation, exhibit three major limitations: (i) meshless shape functions using higher order basis cannot always be computed for arbitrarily distributed nodes (irregular node placement is crucial for facilitating automated discretization of complex geometries); (ii) imposition of the Essential Boundary Conditions (EBC) is not straightforward; and, (iii) numerical (Gauss) integration in space is not exact as meshless shape functions are not polynomial. This paper presents a suite of Meshless Total Lagrangian Explicit Dynamics (MTLED) algorithms incorporating a Modified Moving Least Squares (MMLS) method for interpolating scattered data both for visualization and for numerical computations of soft tissue deformation, a novel way of imposing EBC for explicit time integration, and an adaptive numerical integration procedure within the Meshless Total Lagrangian Explicit Dynamics algorithm. The appropriateness and effectiveness of the proposed methods is demonstrated using comparisons with the established non-linear procedures from commercial finite element software ABAQUS and experiments with very large deformations. To demonstrate the translational benefits of MTLED we also present a realistic brain-shift computation.
journal_name
Med Image Analjournal_title
Medical image analysisauthors
Joldes G,Bourantas G,Zwick B,Chowdhury H,Wittek A,Agrawal S,Mountris K,Hyde D,Warfield SK,Miller Kdoi
10.1016/j.media.2019.06.004subject
Has Abstractpub_date
2019-08-01 00:00:00pages
152-171eissn
1361-8415issn
1361-8423pii
S1361-8415(18)30572-3journal_volume
56pub_type
杂志文章abstract：:Intervention planning is essential for successful Mitral Valve (MV) repair procedures. Finite-element models (FEM) of the MV could be used to achieve this goal, but the translation to the clinical domain is challenging. Many input parameters for the FEM models, such as tissue properties, are not known. In addition, on...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2016.03.011
更新日期：2017-01-01 00:00:00
abstract：:We propose HookNet, a semantic segmentation model for histopathology whole-slide images, which combines context and details via multiple branches of encoder-decoder convolutional neural networks. Concentric patches at multiple resolutions with different fields of view, feed different branches of HookNet, and intermedi...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101890
更新日期：2021-02-01 00:00:00
abstract：:In this paper, we review state-of-the-art techniques to correct eye motion artifacts in Optical Coherence Tomography (OCT) imaging. The methods for eye motion artifact reduction can be categorized into two major classes: (1) hardware-based techniques and (2) software-based techniques. In the first class, additional ha...
journal_title：Medical image analysis
pub_type： 杂志文章,评审
doi：10.1016/j.media.2017.02.002
更新日期：2017-04-01 00:00:00
abstract：:We describe a new magnetic resonance (MR) image analysis tool that produces cortical surface representations with spherical topology from MR images of the human brain. The tool provides a sequence of low-level operations in a single package that can produce accurate brain segmentations in clinical time. The tools incl...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/s1361-8415(02)00054-3
更新日期：2002-06-01 00:00:00
abstract：:It has previously been demonstrated that freehand 3D ultrasound can be acquired without a position sensor by measuring the elevational speckle decorrelation from frame to frame. However, this requires that the B-scans contain significant amounts of fully developed speckle. In this paper, we show that this condition is...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2005.08.001
更新日期：2006-04-01 00:00:00
abstract：:Although white matter hyperintensities evolve in the course of ageing, few solutions exist to consider the lesion segmentation problem longitudinally. Based on an existing automatic lesion segmentation algorithm, a longitudinal extension is proposed. For evaluation purposes, a longitudinal lesion simulator is created ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2017.02.007
更新日期：2017-05-01 00:00:00
abstract：:Magnetic resonance imaging is a popular and powerful non-invasive imaging technique. Automated analysis has become mandatory to efficiently cope with the large amount of data generated using this modality. However, several artifacts, such as intensity non-uniformity, can degrade the quality of acquired data. Intensity...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2005.09.004
更新日期：2006-04-01 00:00:00
abstract：:In order to improve the accuracy of image-guided neurosurgery, different biomechanical models have been developed to correct preoperative images with respect to intraoperative changes like brain shift or tumor resection. All existing biomechanical models simulate different anatomical structures by using either appropr...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/s1361-8415(02)00059-2
更新日期：2002-12-01 00:00:00
abstract：:A novel method based on multiset canonical correlation analysis (mCCA) and linear discriminant analysis (LDA) is presented to identify the major depressive disorder (MDD). The new method comprises two parts, namely, the mCCA-rreg and sparse LDA models. The mCCA-rreg model extends the classical canonical correlation mo...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.101600
更新日期：2020-02-01 00:00:00
abstract：:Ultrasonic techniques are presented for the study of soft biological tissue structure and function. Changes in echo waveforms caused by microscopic variations in the mechanical properties of tissue can reveal disease mechanism, in vivo. On a larger scale, elasticity imaging describes the macroscopic mechanical propert...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/s1361-8415(98)80014-5
更新日期：1998-12-01 00:00:00
abstract：:In this paper, we propose a new strategy for modelling sliding conditions when registering 3D images in a piecewise-diffeomorphic framework. More specifically, our main contribution is the development of a mathematical formalism to perform Large Deformation Diffeomorphic Metric Mapping registration with sliding condit...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2012.10.001
更新日期：2013-02-01 00:00:00
abstract：:Pseudo-healthy synthesis is the task of creating a subject-specific 'healthy' image from a pathological one. Such images can be helpful in tasks such as anomaly detection and understanding changes induced by pathology and disease. In this paper, we present a model that is encouraged to disentangle the information of p...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101719
更新日期：2020-08-01 00:00:00
abstract：:The problem of respiratory motion has proved a serious obstacle in developing techniques to acquire images or guide interventions in abdominal and thoracic organs. Motion models offer a possible solution to these problems, and as a result the field of respiratory motion modelling has become an active one over the past...
journal_title：Medical image analysis
pub_type： 杂志文章,评审
doi：10.1016/j.media.2012.09.005
更新日期：2013-01-01 00:00:00
abstract：:Examinations of the spinal column with both, Magnetic Resonance (MR) imaging and Computed Tomography (CT), often require a precise three-dimensional positioning, angulation and labeling of the spinal disks and the vertebrae. A fully automatic and robust approach is a prerequisite for an automated scan alignment as wel...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2012.09.007
更新日期：2013-12-01 00:00:00
abstract：:Interpretation of ultrasound videos of the fetal heart is crucial for the antenatal diagnosis of congenital heart disease (CHD). We believe that automated image analysis techniques could make an important contribution towards improving CHD detection rates. However, to our knowledge, no previous work has been done in t...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2016.11.006
更新日期：2017-02-01 00:00:00
abstract：:As a common disease in the elderly, neural foramina stenosis (NFS) brings a significantly negative impact on the quality of life due to its symptoms including pain, disability, fall risk and depression. Accurate boundary delineation is essential to the clinical diagnosis and treatment of NFS. However, existing clinica...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2016.10.009
更新日期：2017-02-01 00:00:00
abstract：:In this paper, we present a graph-based concurrent brain tumor segmentation and atlas to diseased patient registration framework. Both segmentation and registration problems are modeled using a unified pairwise discrete Markov Random Field model on a sparse grid superimposed to the image domain. Segmentation is addres...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2014.02.006
更新日期：2014-05-01 00:00:00
abstract：:Images of the retina acquired using optical coherence tomography (OCT) often suffer from intensity inhomogeneity problems that degrade both the quality of the images and the performance of automated algorithms utilized to measure structural changes. This intensity variation has many causes, including off-axis acquisit...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2017.09.008
更新日期：2018-01-01 00:00:00
abstract：:Although there are many algorithms available in the literature aimed at segmentation and model reconstruction of 3D angiographic images, many are focused on characterizing only a part of the vascular network. This study is motivated by the recent emerging prospects of whole-organ simulations in coronary hemodynamics, ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2007.06.012
更新日期：2007-12-01 00:00:00
abstract：:Knowledge of whole heart anatomy is a prerequisite for many clinical applications. Whole heart segmentation (WHS), which delineates substructures of the heart, can be very valuable for modeling and analysis of the anatomy and functions of the heart. However, automating this segmentation can be challenging due to the l...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.101537
更新日期：2019-12-01 00:00:00
abstract：:Accurate digital representation of major white matter bundles in the brain is an important goal in neuroscience image computing since the representations can be used for surgical planning, intra-patient longitudinal analysis and inter-subject population connectivity studies. Reconstructing desired fiber bundles genera...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2018.02.008
更新日期：2018-05-01 00:00:00
abstract：:The accurate localization of anatomical landmarks is a challenging task, often solved by domain specific approaches. We propose a method for the automatic localization of landmarks in complex, repetitive anatomical structures. The key idea is to combine three steps: (1) a classifier for pre-filtering anatomical landma...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2013.02.004
更新日期：2013-12-01 00:00:00
abstract：:A stochastic finite element framework is presented for the simultaneous estimation of the cardiac kinematic functions and material model parameters from periodic medical image sequences. While existing biomechanics studies of the myocardial material constitutive laws have assumed known tissue kinematic measurements, a...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/s1361-8415(03)00066-5
更新日期：2003-12-01 00:00:00
abstract：:Percutaneous coronary intervention is a minimally invasive procedure that is usually performed under image guidance using X-ray angiograms in which coronary arteries are opacified with contrast agent. In X-ray images, 3D objects are projected on a 2D plane, generating semi-transparent layers that overlap each other. T...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2017.04.011
更新日期：2017-07-01 00:00:00
abstract：:In this paper, we present a generative Bayesian approach for estimating the low-dimensional latent space of diffeomorphic shape variability in a population of images. We develop a latent variable model for principal geodesic analysis (PGA) that provides a probabilistic framework for factor analysis in the space of dif...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2015.04.009
更新日期：2015-10-01 00:00:00
abstract：:In this work a new statistic deformable model for 3D segmentation of anatomical organs in medical images is proposed. A statistic discriminant snake performs a supervised learning of the object boundary in an image slice to segment the next slice of the image sequence. Each part of the object boundary is projected in ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/s1361-8415(03)00014-8
更新日期：2003-09-01 00:00:00
abstract：:Simulating cardiac electromechanical activity is of great interest for a better understanding of pathologies and for therapy planning. Design and validation of such models is difficult due to the lack of clinical data. XMR systems are a new type of interventional facility in which patients can be rapidly transferred b...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2005.05.003
更新日期：2005-10-01 00:00:00
abstract：:Dynamical contrast enhanced (DCE) imaging allows non invasive access to tissue micro-vascularization. It appears as a promising tool to build imaging biomarkers for diagnostic, prognosis or anti-angiogenesis treatment monitoring of cancer. However, quantitative analysis of DCE image sequences suffers from low signal t...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2018.10.007
更新日期：2019-01-01 00:00:00
abstract：:An automated segmentation method is presented for multi-organ segmentation in abdominal CT images. Dictionary learning and sparse coding techniques are used in the proposed method to generate target specific priors for segmentation. The method simultaneously learns dictionaries which have reconstructive power and clas...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2015.04.015
更新日期：2015-07-01 00:00:00
abstract：:Accurate segmentation of a pulmonary nodule is an important and active area of research in medical image processing. Although many algorithms have been reported in literature for this problem, those that are applicable to various density types have not been available until recently. In this paper, we propose a new alg...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2010.08.005
更新日期：2011-02-01 00:00:00
