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 non-uniformity consists in anatomically irrelevant intensity variation throughout data. It can be induced by the choice of the radio-frequency coil, the acquisition pulse sequence and by the nature and geometry of the sample itself. Numerous methods have been proposed to correct this artifact. In this paper, we propose an overview of existing methods. We first sort them according to their location in the acquisition/processing pipeline. Sorting is then refined based on the assumptions those methods rely on. Next, we present the validation protocols used to evaluate these different correction schemes both from a qualitative and a quantitative point of view. Finally, availability and usability of the presented methods is discussed.
journal_name
Med Image Analjournal_title
Medical image analysisauthors
Belaroussi B,Milles J,Carme S,Zhu YM,Benoit-Cattin Hdoi
10.1016/j.media.2005.09.004subject
Has Abstractpub_date
2006-04-01 00:00:00pages
234-46issue
2eissn
1361-8415issn
1361-8423pii
S1361-8415(05)00097-6journal_volume
10pub_type
杂志文章abstract::Classification of digital pathology images is imperative in cancer diagnosis and prognosis. Recent advancements in deep learning and computer vision have greatly benefited the pathology workflow by developing automated solutions for classification tasks. However, the cost and time for acquiring high quality task-speci...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2020.101859
更新日期:2021-01-01 00:00:00
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
更新日期:2019-12-01 00:00:00
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
更新日期:2015-12-01 00:00:00
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
更新日期:2018-12-01 00:00:00
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::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::We present an algorithm estimating the width of retinal vessels in fundus camera images. The algorithm uses a novel parametric surface model of the cross-sectional intensities of vessels, and ensembles of bagged decision trees to estimate the local width from the parameters of the best-fit surface. We report comparati...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2013.07.006
更新日期:2013-12-01 00:00:00
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
更新日期:1996-03-01 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::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::Diffusion magnetic resonance imaging (dMRI) provides a noninvasive method for measuring brain tissue microstructure. q-Space deep learning(q-DL) methods have been developed to accurately estimate tissue microstructure from dMRI scans acquired with a reduced number of diffusion gradients. In these methods, deep network...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2020.101885
更新日期:2021-01-01 00:00:00
abstract::Accurate and robust segmentation of abdominal organs on CT is essential for many clinical applications such as computer-aided diagnosis and computer-aided surgery. But this task is challenging due to the weak boundaries of organs, the complexity of the background, and the variable sizes of different organs. To address...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2019.04.005
更新日期:2019-07-01 00:00:00
abstract::Deep learning-based systems can achieve a diagnostic performance comparable to physicians in a variety of medical use cases including the diagnosis of diabetic retinopathy. To be useful in clinical practice, it is necessary to have well calibrated measures of the uncertainty with which these systems report their decis...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2020.101724
更新日期:2020-08-01 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::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
更新日期:2006-04-01 00:00:00
abstract::Analyses of the human tongue motion as captured from 2D dynamic ultrasound data often requires segmentation of the mid-sagittal tongue contours. However, semi-automatic extraction of the tongue shape presents practical challenges. We approach this segmentation problem by proposing a novel higher-order Markov random fi...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2012.07.001
更新日期:2012-12-01 00:00:00
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
更新日期:2020-12-01 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::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::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
更新日期:2013-12-01 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::This paper presents a new approach for multimodal medical image registration and compares it to normalized mutual information (NMI) and the correlation ratio (CR). Like NMI and CR, the new method's measure of registration quality is based on the distribution of points in the joint intensity scatter plot (JISP); compac...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2007.12.002
更新日期:2008-08-01 00:00:00
abstract::In this paper, we exploit the ability of Compressed Sensing (CS) to recover the whole 3D Diffusion MRI (dMRI) signal from a limited number of samples while efficiently recovering important diffusion features such as the Ensemble Average Propagator (EAP) and the Orientation Distribution Function (ODF). Some attempts to...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2013.02.010
更新日期:2013-07-01 00:00:00
abstract::Automated quantitative estimation of spinal curvature is an important task for the ongoing evaluation and treatment planning of Adolescent Idiopathic Scoliosis (AIS). It solves the widely accepted disadvantage of manual Cobb angle measurement (time-consuming and unreliable) which is currently the gold standard for AIS...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2018.05.005
更新日期:2018-08-01 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::A deformable registration method is described that enables automatic alignment of magnetic resonance (MR) and 3D transrectal ultrasound (TRUS) images of the prostate gland. The method employs a novel "model-to-image" registration approach in which a deformable model of the gland surface, derived from an MR image, is r...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2010.11.003
更新日期:2012-04-01 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::The goal of this study is to provide a theoretical framework for accurately optimizing the segmentation energy considering all of the possible shapes generated from the level-set-based statistical shape model (SSM). The proposed algorithm solves the well-known open problem, in which a shape prior may not be optimal in...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2015.11.003
更新日期:2016-02-01 00:00:00
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
更新日期:2019-10-01 00:00:00
abstract::Surgical tool detection is attracting increasing attention from the medical image analysis community. The goal generally is not to precisely locate tools in images, but rather to indicate which tools are being used by the surgeon at each instant. The main motivation for annotating tool usage is to design efficient sol...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2018.11.008
更新日期:2019-02-01 00:00:00