A spatiotemporal statistical atlas of motion for the quantification of abnormal myocardial tissue velocities.

Abstract:

:In this paper, we present a new method for the automatic comparison of myocardial motion patterns and the characterization of their degree of abnormality, based on a statistical atlas of motion built from a reference healthy population. Our main contribution is the computation of atlas-based indexes that quantify the abnormality in the motion of a given subject against a reference population, at every location in time and space. The critical computational cost inherent to the construction of an atlas is highly reduced by the definition of myocardial velocities under a small displacements hypothesis. The indexes we propose are of notable interest for the assessment of anomalies in cardiac mobility and synchronicity when applied, for instance, to candidate selection for cardiac resynchronization therapy (CRT). We built an atlas of normality using 2D ultrasound cardiac sequences from 21 healthy volunteers, to which we compared 14 CRT candidates with left ventricular dyssynchrony (LVDYS). We illustrate the potential of our approach in characterizing septal flash, a specific motion pattern related to LVDYS and recently introduced as a very good predictor of response to CRT.

journal_name

Med Image Anal

journal_title

Medical image analysis

authors

Duchateau N,De Craene M,Piella G,Silva E,Doltra A,Sitges M,Bijnens BH,Frangi AF

doi

10.1016/j.media.2010.12.006

subject

Has Abstract

pub_date

2011-06-01 00:00:00

pages

316-28

issue

3

eissn

1361-8415

issn

1361-8423

pii

S1361-8415(10)00136-2

journal_volume

15

pub_type

杂志文章
  • Ω-Net (Omega-Net): Fully automatic, multi-view cardiac MR detection, orientation, and segmentation with deep neural networks.

    abstract::Pixelwise segmentation of the left ventricular (LV) myocardium and the four cardiac chambers in 2-D steady state free precession (SSFP) cine sequences is an essential preprocessing step for a wide range of analyses. Variability in contrast, appearance, orientation, and placement of the heart between patients, clinical...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2018.05.008

    authors: Vigneault DM,Xie W,Ho CY,Bluemke DA,Noble JA

    更新日期:2018-08-01 00:00:00

  • Suite of meshless algorithms for accurate computation of soft tissue deformation for surgical simulation.

    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...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2019.06.004

    authors: Joldes G,Bourantas G,Zwick B,Chowdhury H,Wittek A,Agrawal S,Mountris K,Hyde D,Warfield SK,Miller K

    更新日期:2019-08-01 00:00:00

  • Automated classification of lung bronchovascular anatomy in CT using AdaBoost.

    abstract::Lung CAD systems require the ability to classify a variety of pulmonary structures as part of the diagnostic process. The purpose of this work was to develop a methodology for fully automated voxel-by-voxel classification of airways, fissures, nodules, and vessels from chest CT images using a single feature set and cl...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2007.03.004

    authors: Ochs RA,Goldin JG,Abtin F,Kim HJ,Brown K,Batra P,Roback D,McNitt-Gray MF,Brown MS

    更新日期:2007-06-01 00:00:00

  • Segmentation of the skull in MRI volumes using deformable model and taking the partial volume effect into account.

    abstract::Segmentation of the skull in medical imagery is an important stage in applications that require the construction of realistic models of the head. Such models are used, for example, to simulate the behavior of electro-magnetic fields in the head and to model the electrical activity of the cortex in EEG and MEG data. In...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/s1361-8415(00)00016-5

    authors: Rifa H,Bloch I,Hutchinson S,Wiart J,Garnero L

    更新日期:2000-09-01 00:00:00

  • Gaussianization of Diffusion MRI Data Using Spatially Adaptive Filtering.

    abstract::Diffusion MRI magnitude data, typically Rician or noncentral χ distributed, is affected by the noise floor, which falsely elevates signal, reduces image contrast, and biases estimation of diffusion parameters. Noise floor can be avoided by extracting real-valued Gaussian-distributed data from complex diffusion-weighte...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2020.101828

    authors: Liu F,Feng J,Chen G,Shen D,Yap PT

    更新日期:2021-02-01 00:00:00

  • Hierarchical spherical deformation for cortical surface registration.

    abstract::We present hierarchical spherical deformation for a group-wise shape correspondence to address template selection bias and to minimize registration distortion. In this work, we aim at a continuous and smooth deformation field to guide accurate cortical surface registration. In conventional spherical registration metho...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2019.06.013

    authors: Lyu I,Kang H,Woodward ND,Styner MA,Landman BA

    更新日期:2019-10-01 00:00:00

  • Hierarchical performance estimation in the statistical label fusion framework.

    abstract::Label fusion is a critical step in many image segmentation frameworks (e.g., multi-atlas segmentation) as it provides a mechanism for generalizing a collection of labeled examples into a single estimate of the underlying segmentation. In the multi-label case, typical label fusion algorithms treat all labels equally - ...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2014.06.005

    authors: Asman AJ,Landman BA

    更新日期:2014-10-01 00:00:00

  • Computer technology in detection and staging of prostate carcinoma: a review.

    abstract::After two decades of increasing interest and research activity, computer-assisted diagnostic approaches are reaching the stage where more routine deployment in clinical practice is becoming a possibility [Kruppinski, E.A., 2004. Computer-aided detection in clinical environment: Benefits and challenges for radiologists...

    journal_title:Medical image analysis

    pub_type: 杂志文章,评审

    doi:10.1016/j.media.2005.06.003

    authors: Zhu Y,Williams S,Zwiggelaar R

    更新日期:2006-04-01 00:00:00

  • Dynamically constructed network with error correction for accurate ventricle volume estimation.

    abstract::Automated ventricle volume estimation (AVVE) on cardiac magnetic resonance (CMR) images is very important for clinical cardiac disease diagnosis. However, current AVVE methods ignore the error correction for the estimated volume. This results in clinically intolerable ventricle volume estimation error and further lead...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2020.101723

    authors: Luo G,Wang W,Tam C,Wang K,Cao S,Zhang H,Chen B,Li S

    更新日期:2020-08-01 00:00:00

  • Involuntary eye motion correction in retinal optical coherence tomography: Hardware or software solution?

    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

    authors: Baghaie A,Yu Z,D'Souza RM

    更新日期:2017-04-01 00:00:00

  • Intensity non-uniformity correction in MRI: existing methods and their validation.

    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

    authors: Belaroussi B,Milles J,Carme S,Zhu YM,Benoit-Cattin H

    更新日期:2006-04-01 00:00:00

  • Self-similarity weighted mutual information: a new nonrigid image registration metric.

    abstract::Mutual information (MI) has been widely used as a similarity measure for rigid registration of multi-modal and uni-modal medical images. However, robust application of MI to deformable registration is challenging mainly because rich structural information, which are critical cues for successful deformable registration...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2013.12.003

    authors: Rivaz H,Karimaghaloo Z,Collins DL

    更新日期:2014-02-01 00:00:00

  • Recovering from missing data in population imaging - Cardiac MR image imputation via conditional generative adversarial nets.

    abstract::Accurate ventricular volume measurements are the primary indicators of normal/abnor- mal cardiac function and are dependent on the Cardiac Magnetic Resonance (CMR) volumes being complete. However, missing or unusable slices owing to the presence of image artefacts such as respiratory or motion ghosting, aliasing, ring...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2020.101812

    authors: Xia Y,Zhang L,Ravikumar N,Attar R,Piechnik SK,Neubauer S,Petersen SE,Frangi AF

    更新日期:2021-01-01 00:00:00

  • Symmetric positive semi-definite Cartesian Tensor fiber orientation distributions (CT-FOD).

    abstract::A novel method for estimating a field of fiber orientation distribution (FOD) based on signal de-convolution from a given set of diffusion weighted magnetic resonance (DW-MR) images is presented. We model the FOD by higher order Cartesian tensor basis using a parametrization that explicitly enforces the positive semi-...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2012.07.002

    authors: Weldeselassie YT,Barmpoutis A,Atkins MS

    更新日期:2012-08-01 00:00:00

  • Ultrasonic and elasticity imaging to model disease-induced changes in soft-tissue structure.

    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

    authors: Chaturvedi P,Insana MF,Hall TJ

    更新日期:1998-12-01 00:00:00

  • Robust registration procedures for endoscopic imaging.

    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

    authors: Konen W,Tombrock S,Scholz M

    更新日期:2007-12-01 00:00:00

  • Manifold modeling for brain population analysis.

    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

    authors: Gerber S,Tasdizen T,Thomas Fletcher P,Joshi S,Whitaker R,Alzheimers Disease Neuroimaging Initiative (ADNI).

    更新日期:2010-10-01 00:00:00

  • Non-invasive estimation of relative pressure in turbulent flow using virtual work-energy.

    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

    authors: Marlevi D,Ha H,Dillon-Murphy D,Fernandes JF,Fovargue D,Colarieti-Tosti M,Larsson M,Lamata P,Figueroa CA,Ebbers T,Nordsletten DA

    更新日期:2020-02-01 00:00:00

  • Improved fidelity of brain microstructure mapping from single-shell diffusion MRI.

    abstract::Diffusion weighted imaging (DWI) is sensitive to alterations in the diffusion of water molecules caused by microstructural barriers. Different microstructural compartments are characterized by differences in DWI signal. Diffusion tensor imaging conflates the signal from these compartments into a single tensor, which p...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2015.10.004

    authors: Taquet M,Scherrer B,Boumal N,Peters JM,Macq B,Warfield SK

    更新日期:2015-12-01 00:00:00

  • Fusion of white and gray matter geometry: a framework for investigating brain development.

    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

    authors: Savadjiev P,Rathi Y,Bouix S,Smith AR,Schultz RT,Verma R,Westin CF

    更新日期:2014-12-01 00:00:00

  • Global localization of 3D anatomical structures by pre-filtered Hough forests and discrete optimization.

    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

    authors: Donner R,Menze BH,Bischof H,Langs G

    更新日期:2013-12-01 00:00:00

  • Adaptive, template moderated, spatially varying statistical classification.

    abstract::A novel image segmentation algorithm was developed to allow the automatic segmentation of both normal and abnormal anatomy from medical images. The new algorithm is a form of spatially varying statistical classification, in which an explicit anatomical template is used to moderate the segmentation obtained by statisti...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/s1361-8415(00)00003-7

    authors: Warfield SK,Kaus M,Jolesz FA,Kikinis R

    更新日期:2000-03-01 00:00:00

  • Segmentation of the visible human for high-quality volume-based visualization.

    abstract::This article describes a combination of interactive classification and super-sampling visualization algorithms that greatly enhances the realism of 3-D reconstructions of the Visible Human data sets. Objects are classified on the basis of ellipsoidal regions in RGB space. The ellipsoids are used for super-sampling in ...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/s1361-8415(97)85001-3

    authors: Schiemann T,Tiede U,Höhne KH

    更新日期:1997-09-01 00:00:00

  • Interactive training system for interventional electrocardiology procedures.

    abstract::Recent progress in cardiac catheterization and devices has allowed the development of new therapies for severe cardiac diseases like arrhythmias and heart failure. The skills required for such interventions are very challenging to learn, and are typically acquired over several years. Virtual reality simulators may red...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2016.06.040

    authors: Talbot H,Spadoni F,Duriez C,Sermesant M,O'Neill M,Jaïs P,Cotin S,Delingette H

    更新日期:2017-01-01 00:00:00

  • Quantitative analysis of retinal OCT.

    abstract::Clinical acceptance of 3-D OCT retinal imaging brought rapid development of quantitative 3-D analysis of retinal layers, vasculature, retinal lesions as well as facilitated new research in retinal diseases. One of the cornerstones of many such analyses is segmentation and thickness quantification of retinal layers and...

    journal_title:Medical image analysis

    pub_type: 社论

    doi:10.1016/j.media.2016.06.001

    authors: Sonka M,Abràmoff MD

    更新日期:2016-10-01 00:00:00

  • A gradient-based optical-flow cardiac motion estimation method for cine and tagged MR images.

    abstract::A new method is proposed to quantify the myocardial motion from both 2D C(ine)-MRI and T(agged)-MRI sequences. The tag pattern offers natural landmarks within the image that makes it possible to accurately quantify the motion within the myocardial wall. Therefore, several methods have been proposed for T-MRI. However,...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2019.06.016

    authors: Wang L,Clarysse P,Liu Z,Gao B,Liu W,Croisille P,Delachartre P

    更新日期:2019-10-01 00:00:00

  • Towards cross-modal organ translation and segmentation: A cycle- and shape-consistent generative adversarial network.

    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

    authors: Cai J,Zhang Z,Cui L,Zheng Y,Yang L

    更新日期:2019-02-01 00:00:00

  • Automated voxel-based 3D cortical thickness measurement in a combined Lagrangian-Eulerian PDE approach using partial volume maps.

    abstract::Accurate cortical thickness estimation is important for the study of many neurodegenerative diseases. Many approaches have been previously proposed, which can be broadly categorised as mesh-based and voxel-based. While the mesh-based approaches can potentially achieve subvoxel resolution, they usually lack the computa...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2009.07.003

    authors: Acosta O,Bourgeat P,Zuluaga MA,Fripp J,Salvado O,Ourselin S,Alzheimer's Disease Neuroimaging Initiative.

    更新日期:2009-10-01 00:00:00

  • Groupwise multi-atlas segmentation of the spinal cord's internal structure.

    abstract::The spinal cord is an essential and vulnerable component of the central nervous system. Differentiating and localizing the spinal cord internal structure (i.e., gray matter vs. white matter) is critical for assessment of therapeutic impacts and determining prognosis of relevant conditions. Fortunately, new magnetic re...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2014.01.003

    authors: Asman AJ,Bryan FW,Smith SA,Reich DS,Landman BA

    更新日期:2014-04-01 00:00:00

  • Towards intelligent robust detection of anatomical structures in incomplete volumetric data.

    abstract::Robust and fast detection of anatomical structures represents an important component of medical image analysis technologies. Current solutions for anatomy detection are based on machine learning, and are generally driven by suboptimal and exhaustive search strategies. In particular, these techniques do not effectively...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2018.06.007

    authors: Ghesu FC,Georgescu B,Grbic S,Maier A,Hornegger J,Comaniciu D

    更新日期:2018-08-01 00:00:00