当前位置： SCI文献检索 > MEDICAL IMAGE ANALYSIS期刊下所有文献 > Local spatio-temporal encoding of raw perfusion MRI for the prediction of final lesion in stroke.

Local spatio-temporal encoding of raw perfusion MRI for the prediction of final lesion in stroke.

Abstract：

:We address the medical image analysis issue of predicting the final lesion in stroke from early perfusion magnetic resonance imaging. The classical processing approach for the dynamical perfusion images consists in a temporal deconvolution to improve the temporal signals associated with each voxel before performing prediction. We demonstrate here the value of exploiting directly the raw perfusion data by encoding the local environment of each voxel as a spatio-temporal texture, with an observation scale larger than the voxel. As a first illustration for this approach, the textures are characterized with local binary patterns and the classification is performed using a standard support vector machine (SVM). This simple machine learning classification scheme demonstrates results with 95% accuracy on average while working only raw perfusion data. We discuss the influence of the observation scale and evaluate the interest of using post-processed perfusion data with this approach.

journal_name

Med Image Anal

journal_title

Medical image analysis

authors

Giacalone M,Rasti P,Debs N,Frindel C,Cho TH,Grenier E,Rousseau D

doi

10.1016/j.media.2018.08.008

subject

Has Abstract

pub_date

2018-12-01 00:00:00

pages

117-126

eissn

1361-8415

issn

1361-8423

pii

S1361-8415(18)30680-7

journal_volume

50

pub_type

杂志文章

相关文献

MEDICAL IMAGE ANALYSIS文献大全
  • 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

  • Equilibrated warping: Finite element image registration with finite strain equilibrium gap regularization.

    abstract：:In this paper, we propose a novel continuum finite strain formulation of the equilibrium gap regularization for image registration. The equilibrium gap regularization essentially penalizes any deviation from the solution of a hyperelastic body in equilibrium with arbitrary loads prescribed at the boundary. It thus rep...

    journal_title：Medical image analysis

    pub_type： 杂志文章

    doi：10.1016/j.media.2018.07.007

    authors： Genet M,Stoeck CT,von Deuster C,Lee LC,Kozerke S

    更新日期：2018-12-01 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

  • Attentive neural cell instance segmentation.

    abstract：:Neural cell instance segmentation, which aims at joint detection and segmentation of every neural cell in a microscopic image, is essential to many neuroscience applications. The challenge of this task involves cell adhesion, cell distortion, unclear cell contours, low-contrast cell protrusion structures, and backgrou...

    journal_title：Medical image analysis

    pub_type： 杂志文章

    doi：10.1016/j.media.2019.05.004

    authors： Yi J,Wu P,Jiang M,Huang Q,Hoeppner DJ,Metaxas DN

    更新日期：2019-07-01 00:00:00

  • Neighborhood resolved fiber orientation distributions (NRFOD) in automatic labeling of white matter fiber pathways.

    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

    authors： Ugurlu D,Firat Z,Türe U,Unal G

    更新日期：2018-05-01 00:00:00

  • Automatic online layer separation for vessel enhancement in X-ray angiograms for percutaneous coronary interventions.

    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

    authors： Ma H,Hoogendoorn A,Regar E,Niessen WJ,van Walsum T

    更新日期：2017-07-01 00:00:00

  • Automatic segmentation of 3D micro-CT coronary vascular images.

    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

    authors： Lee J,Beighley P,Ritman E,Smith N

    更新日期：2007-12-01 00:00:00

  • DT-MRI denoising and neuronal fiber tracking.

    abstract：:Diffusion tensor imaging can provide the fundamental information required for viewing structural connectivity. However, robust and accurate acquisition and processing algorithms are needed to accurately map the nerve connectivity. In this paper, we present a novel algorithm for extracting and visualizing the fiber tra...

    journal_title：Medical image analysis

    pub_type： 杂志文章

    doi：10.1016/j.media.2003.12.001

    authors： McGraw T,Vemuri BC,Chen Y,Rao M,Mareci T

    更新日期：2004-06-01 00:00:00

  • Sensorless freehand 3D ultrasound in real tissue: speckle decorrelation without fully developed speckle.

    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

    authors： Gee AH,James Housden R,Hassenpflug P,Treece GM,Prager RW

    更新日期：2006-04-01 00:00:00

  • Advances and challenges in deformable image registration: From image fusion to complex motion modelling.

    abstract：:Over the past 20 years, the field of medical image registration has significantly advanced from multi-modal image fusion to highly non-linear, deformable image registration for a wide range of medical applications and imaging modalities, involving the compensation and analysis of physiological organ motion or of tissu...

    journal_title：Medical image analysis

    pub_type： 社论

    doi：10.1016/j.media.2016.06.031

    authors： Schnabel JA,Heinrich MP,Papież BW,Brady SJM

    更新日期：2016-10-01 00:00:00

  • Automated model-based vertebra detection, identification, and segmentation in CT images.

    abstract：:For many orthopaedic, neurological, and oncological applications, an exact segmentation of the vertebral column including an identification of each vertebra is essential. However, although bony structures show high contrast in CT images, the segmentation and labelling of individual vertebrae is challenging. In this pa...

    journal_title：Medical image analysis

    pub_type： 杂志文章

    doi：10.1016/j.media.2009.02.004

    authors： Klinder T,Ostermann J,Ehm M,Franz A,Kneser R,Lorenz C

    更新日期：2009-06-01 00:00:00

  • Quantitative analysis of multi-spectral fundus images.

    abstract：:We have developed a new technique for extracting histological parameters from multi-spectral images of the ocular fundus. The new method uses a Monte Carlo simulation of the reflectance of the fundus to model how the spectral reflectance of the tissue varies with differing tissue histology. The model is parameterised ...

    journal_title：Medical image analysis

    pub_type： 杂志文章

    doi：10.1016/j.media.2006.05.007

    authors： Styles IB,Calcagni A,Claridge E,Orihuela-Espina F,Gibson JM

    更新日期：2006-08-01 00:00:00

  • An efficient Riemannian statistical shape model using differential coordinates: With application to the classification of data from the Osteoarthritis Initiative.

    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

    authors： von Tycowicz C,Ambellan F,Mukhopadhyay A,Zachow S

    更新日期：2018-01-01 00:00:00

  • High resolution cortical bone thickness measurement from clinical CT data.

    abstract：:The distribution of cortical bone in the proximal femur is believed to be a critical component in determining fracture resistance. Current CT technology is limited in its ability to measure cortical thickness, especially in the sub-millimetre range which lies within the point spread function of today's clinical scanne...

    journal_title：Medical image analysis

    pub_type： 杂志文章

    doi：10.1016/j.media.2010.01.003

    authors： Treece GM,Gee AH,Mayhew PM,Poole KE

    更新日期：2010-06-01 00:00:00

  • Dynamic MRI reconstruction with end-to-end motion-guided network.

    abstract：:Temporal correlation in dynamic magnetic resonance imaging (MRI), such as cardiac MRI, is informative and important to understand motion mechanisms of body regions. Modeling such information into the MRI reconstruction process produces temporally coherent image sequence and reduces imaging artifacts and blurring. Howe...

    journal_title：Medical image analysis

    pub_type： 杂志文章

    doi：10.1016/j.media.2020.101901

    authors： Huang Q,Xian Y,Yang D,Qu H,Yi J,Wu P,Metaxas DN

    更新日期：2021-02-01 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

  • Noise reduction in diffusion MRI using non-local self-similar information in joint x-q space.

    abstract：:Diffusion MRI affords valuable insights into white matter microstructures, but suffers from low signal-to-noise ratio (SNR), especially at high diffusion weighting (i.e., b-value). To avoid time-intensive repeated acquisition, post-processing algorithms are often used to reduce noise. Among existing methods, non-local...

    journal_title：Medical image analysis

    pub_type： 杂志文章

    doi：10.1016/j.media.2019.01.006

    authors： Chen G,Wu Y,Shen D,Yap PT

    更新日期：2019-04-01 00:00:00

  • Capturing intraoperative deformations: research experience at Brigham and Women's Hospital.

    abstract：:During neurosurgical procedures the objective of the neurosurgeon is to achieve the resection of as much diseased tissue as possible while achieving the preservation of healthy brain tissue. The restricted capacity of the conventional operating room to enable the surgeon to visualize critical healthy brain structures ...

    journal_title：Medical image analysis

    pub_type： 杂志文章,评审

    doi：10.1016/j.media.2004.11.005

    authors： Warfield SK,Haker SJ,Talos IF,Kemper CA,Weisenfeld N,Mewes AU,Goldberg-Zimring D,Zou KH,Westin CF,Wells WM,Tempany CM,Golby A,Black PM,Jolesz FA,Kikinis R

    更新日期：2005-04-01 00:00:00

  • LinSEM: Linearizing segmentation evaluation metrics for medical images.

    abstract：:Numerous algorithms are available for segmenting medical images. Empirical discrepancy metrics are commonly used in measuring the similarity or difference between segmentations by algorithms and "true" segmentations. However, one issue with the commonly used metrics is that the same metric value often represents diffe...

    journal_title：Medical image analysis

    pub_type： 杂志文章

    doi：10.1016/j.media.2019.101601

    authors： Li J,Udupa JK,Tong Y,Wang L,Torigian DA

    更新日期：2020-02-01 00:00:00

  • Dual-core steered non-rigid registration for multi-modal images via bi-directional image synthesis.

    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

    authors： Cao X,Yang J,Gao Y,Guo Y,Wu G,Shen D

    更新日期：2017-10-01 00:00:00

  • Adaptive local window for level set segmentation of CT and MRI liver lesions.

    abstract：:We propose a novel method, the adaptive local window, for improving level set segmentation technique. The window is estimated separately for each contour point, over iterations of the segmentation process, and for each individual object. Our method considers the object scale, the spatial texture, and the changes of th...

    journal_title：Medical image analysis

    pub_type： 杂志文章

    doi：10.1016/j.media.2017.01.002

    authors： Hoogi A,Beaulieu CF,Cunha GM,Heba E,Sirlin CB,Napel S,Rubin DL

    更新日期：2017-04-01 00:00:00

  • Towards model-based analysis of cardiac MR tagging data: relation between left ventricular shear strain and myofiber orientation.

    abstract：:Many cardiac pathologies are reflected in abnormal myocardial deformation, accessible through magnetic resonance tagging (MRT). Interpretation of the MRT data is difficult, since the relation between pathology and deformation is not straightforward. Mathematical models of cardiac mechanics could be used to translate m...

    journal_title：Medical image analysis

    pub_type： 杂志文章

    doi：10.1016/j.media.2006.04.001

    authors： Ubbink SW,Bovendeerd PH,Delhaas T,Arts T,van de Vosse FN

    更新日期：2006-08-01 00:00:00

  • Concurrent tumor segmentation and registration with uncertainty-based sparse non-uniform graphs.

    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

    authors： Parisot S,Wells W 3rd,Chemouny S,Duffau H,Paragios N

    更新日期：2014-05-01 00:00:00

  • Unmixing dynamic PET images with variable specific binding kinetics.

    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

    authors： Cavalcanti YC,Oberlin T,Dobigeon N,Stute S,Ribeiro M,Tauber C

    更新日期：2018-10-01 00:00:00

  • Automated landmarking and labeling of fully and partially scanned spinal columns in CT images.

    abstract：:The spinal column is one of the most distinguishable structures in CT scans of the superior part of the human body. It is not necessary to segment the spinal column in order to use it as a frame of reference. It is sufficient to place landmarks and the appropriate anatomical labels at intervertebral disks and vertebra...

    journal_title：Medical image analysis

    pub_type： 杂志文章

    doi：10.1016/j.media.2013.07.005

    authors： Major D,Hladůvka J,Schulze F,Bühler K

    更新日期：2013-12-01 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

  • Integrating segmentation methods from the Insight Toolkit into a visualization application.

    abstract：:The Insight Toolkit (ITK) initiative from the National Library of Medicine has provided a suite of state-of-the-art segmentation and registration algorithms ideally suited to volume visualization and analysis. A volume visualization application that effectively utilizes these algorithms provides many benefits: it allo...

    journal_title：Medical image analysis

    pub_type： 杂志文章

    doi：10.1016/j.media.2005.04.009

    authors： Martin K,Ibáñez L,Avila L,Barré S,Kaspersen JH

    更新日期：2005-12-01 00:00:00

  • Disentangled representation learning in cardiac image analysis.

    abstract：:Typically, a medical image offers spatial information on the anatomy (and pathology) modulated by imaging specific characteristics. Many imaging modalities including Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) can be interpreted in this way. We can venture further and consider that a medical image na...

    journal_title：Medical image analysis

    pub_type： 杂志文章

    doi：10.1016/j.media.2019.101535

    authors： Chartsias A,Joyce T,Papanastasiou G,Semple S,Williams M,Newby DE,Dharmakumar R,Tsaftaris SA

    更新日期：2019-12-01 00:00:00

  • Group-level cortical surface parcellation with sulcal pits labeling.

    abstract：:Sulcal pits are the points of maximal depth within the folds of the cortical surface. These shape descriptors give a unique opportunity to access to a rich, fine-scale representation of the geometry and the developmental milestones of the cortical surface. However, using sulcal pits analysis at group level requires ne...

    journal_title：Medical image analysis

    pub_type： 杂志文章

    doi：10.1016/j.media.2020.101749

    authors： Kaltenmark I,Deruelle C,Brun L,Lefèvre J,Coulon O,Auzias G

    更新日期：2020-12-01 00:00:00

  • Multi-modal volume registration by maximization of mutual information.

    abstract：:A new information-theoretic approach is presented for finding the registration of volumetric medical images of differing modalities. Registration is achieved by adjustment of the relative position and orientation until the mutual information between the images is maximized. In our derivation of the registration proced...

    journal_title：Medical image analysis

    pub_type： 杂志文章

    doi：10.1016/s1361-8415(01)80004-9

    authors： Wells WM 3rd,Viola P,Atsumi H,Nakajima S,Kikinis R

    更新日期：1996-03-01 00:00:00