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 between X-ray and MR systems. Our goal is to design and validate an electromechanical model of the myocardium using XMR imaging. The proposed model is computationally fast and uses clinically observable parameters. We present the integration of anatomy, electrophysiology, and motion from patient data. Pathologies are introduced in the model and simulations are compared to measured data. Initial qualitative comparison on the two clinical cases presented is encouraging. Once fully validated, these models will make it possible to simulate different interventional strategies.
journal_name
Med Image Analjournal_title
Medical image analysisauthors
Sermesant M,Rhode K,Sanchez-Ortiz GI,Camara O,Andriantsimiavona R,Hegde S,Rueckert D,Lambiase P,Bucknall C,Rosenthal E,Delingette H,Hill DL,Ayache N,Razavi Rdoi
10.1016/j.media.2005.05.003subject
Has Abstractpub_date
2005-10-01 00:00:00pages
467-80issue
5eissn
1361-8415issn
1361-8423pii
S1361-8415(05)00064-2journal_volume
9pub_type
杂志文章abstract：:Current neuroimaging investigation of the white matter typically focuses on measurements derived from diffusion tensor imaging, such as fractional anisotropy (FA). In contrast, imaging studies of the gray matter oftentimes focus on morphological features such as cortical thickness, folding and surface curvature. As a ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2014.06.013
更新日期：2014-12-01 00:00:00
abstract：:Deep learning based methods have improved the estimation of tissue microstructure from diffusion magnetic resonance imaging (dMRI) scans acquired with a reduced number of diffusion gradients. These methods learn the mapping from diffusion signals in a voxel or patch to tissue microstructure measures. In particular, it...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101650
更新日期：2020-04-01 00:00:00
abstract：:Graph-based groupwise registration methods are widely used in atlas construction. Given a group of images, a graph is built whose nodes represent the images, and whose edges represent a geodesic path between two nodes. The distribution of images on an image manifold is explored through edge traversal in a graph. The f...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101711
更新日期：2020-08-01 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：:In this paper, we present a framework to estimate local ventricular myocardium contractility using clinical MRI, a heart model and data assimilation. First, we build a generic anatomical model of the ventricles including muscle fibre orientations and anatomical subdivisions. Then, this model is deformed to fit a clini...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2006.04.002
更新日期：2006-08-01 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 propose two information theoretic similarity measures that allow to incorporate tissue class information in non-rigid image registration. The first measure assumes that tissue class probabilities have been assigned to each of the images to be registered by prior segmentation of both of them. One image is then non-r...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2005.03.004
更新日期：2006-06-01 00:00:00
abstract：:This paper presents a symbolic visualization environment known as the Corner Cube environment, which was developed to facilitate rapid examination and comparison of activated foci defined by analyses of functional neuroimaging datasets. We have performed a comparative evaluation of this environment against maximum-int...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/s1361-8415(98)80020-0
更新日期：1998-09-01 00:00:00
abstract：:We propose a novel Riemannian framework for statistical analysis of shapes that is able to account for the nonlinearity in shape variation. By adopting a physical perspective, we introduce a differential representation that puts the local geometric variability into focus. We model these differential coordinates as ele...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2017.09.004
更新日期：2018-01-01 00:00:00
abstract：:We have developed a new computer-aided diagnosis scheme for automated detection of lung nodules in digital chest radiographs based on a combination of morphological features and the wavelet snake. In our scheme, two processes were applied in parallel to reduce the false-positive detections after initial nodule candida...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/s1361-8415(02)00064-6
更新日期：2002-12-01 00:00:00
abstract：:Vascular pressure differences are established risk markers for a number of cardiovascular diseases. Relative pressures are, however, often driven by turbulence-induced flow fluctuations, where conventional non-invasive methods may yield inaccurate results. Recently, we proposed a novel method for non-turbulent flows, ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.101627
更新日期：2020-02-01 00:00:00
abstract：:We propose in this article a content-based image retrieval (CBIR) method for diagnosis aid in medical fields. In the proposed system, images are indexed in a generic fashion, without extracting domain-specific features: a signature is built for each image from its wavelet transform. These image signatures characterize...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2009.11.004
更新日期：2010-04-01 00:00:00
abstract：:Machine learning techniques have been widely used to detect morphological abnormalities from structural brain magnetic resonance imaging data and to support the diagnosis of neurological diseases such as dementia. In this paper, we propose to use a multiple instance learning (MIL) method in an application for the dete...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2014.04.006
更新日期：2014-07-01 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：:Synthesized medical images have several important applications. For instance, they can be used as an intermedium in cross-modality image registration or used as augmented training samples to boost the generalization capability of a classifier. In this work, we propose a generic cross-modality synthesis approach with t...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2018.12.002
更新日期：2019-02-01 00:00:00
abstract：:In prostate cancer radiotherapy, computed tomography (CT) is widely used for dose planning purposes. However, because CT has low soft tissue contrast, it makes manual contouring difficult for major pelvic organs. In contrast, magnetic resonance imaging (MRI) provides high soft tissue contrast, which makes it ideal for...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2017.05.004
更新日期：2017-10-01 00:00:00
abstract：:Discrete optimisation strategies have a number of advantages over their continuous counterparts for deformable registration of medical images. For example: it is not necessary to compute derivatives of the similarity term; dense sampling of the search space reduces the risk of becoming trapped in local optima; and (in...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2015.09.005
更新日期：2016-01-01 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：:In this study, we propose a novel anomaly detection model targeting subtle brain lesions in multiparametric MRI. To compensate for the lack of annotated data adequately sampling the heterogeneity of such pathologies, we cast this problem as an outlier detection problem and introduce a novel configuration of unsupervis...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.101618
更新日期：2020-02-01 00:00:00
abstract：:To analyze dynamic positron emission tomography (PET) images, various generic multivariate data analysis techniques have been considered in the literature, such as principal component analysis (PCA), independent component analysis (ICA), factor analysis and nonnegative matrix factorization (NMF). Nevertheless, these c...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2018.07.011
更新日期：2018-10-01 00:00:00
abstract：:Image registration is an important task in medical image analysis. Whereas most methods are designed for the registration of two images (pairwise registration), there is an increasing interest in simultaneously aligning more than two images using groupwise registration. Multimodal registration in a groupwise setting r...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2018.02.003
更新日期：2018-05-01 00:00:00
abstract：:Image-based parcellation of the brain often leads to multiple disconnected anatomical structures, which pose significant challenges for analyses of morphological shapes. Existing shape models, such as the widely used spherical harmonic (SPHARM) representation, assume topological invariance, so are unable to simultaneo...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2015.02.004
更新日期：2015-05-01 00:00:00
abstract：:Accurate vertebral body (VB) detection and segmentation are critical for spine disease identification and diagnosis. Existing automatic VB detection and segmentation methods may cause false-positive results to the background tissue or inaccurate results to the desirable VB. Because they usually cannot take both the gl...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101861
更新日期：2021-01-01 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：: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：:This paper presents a robust algorithm for calibration and system registration of endoscopic imaging devices. The system registration allows us to map accurately each point in the world coordinate system into the endoscope image and vice versa to obtain the world line of sight for each image pixel. The key point of ou...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2007.04.006
更新日期：2007-12-01 00:00:00
abstract：:A multiple hypothesis tracking approach to the segmentation of small 3D vessel structures is presented. By simultaneously tracking multiple hypothetical vessel trajectories, low contrast passages can be traversed, leading to an improved tracking performance in areas of low contrast. This work also contributes a novel ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2009.12.003
更新日期：2010-04-01 00:00:00
abstract：:Three dimensional Polarized Light Imaging (3D-PLI) is an optical technique which allows mapping the spatial fiber architecture of fibrous postmortem tissues, at sub-millimeter resolutions. Here, we propose an analytical and fast approach to compute the fiber orientation distribution (FOD) from high-resolution vector d...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101760
更新日期：2020-10-01 00:00:00
abstract：:Accurate segmentation of the prostate and organs at risk (e.g., bladder and rectum) in CT images is a crucial step for radiation therapy in the treatment of prostate cancer. However, it is a very challenging task due to unclear boundaries, large intra- and inter-patient shape variability, and uncertain existence of bo...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.03.003
更新日期：2019-05-01 00:00:00
abstract：:This paper describes a method for building efficient representations of large sets of brain images. Our hypothesis is that the space spanned by a set of brain images can be captured, to a close approximation, by a low-dimensional, nonlinear manifold. This paper presents a method to learn such a low-dimensional manifol...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2010.05.008
更新日期：2010-10-01 00:00:00
