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 leads to wrong ejection fraction (EF) assessment, which significantly limits the application potential of AVVE methods. The objective of this paper is to address this problem with AVVE and further make it more clinically applicable. We proposed a dynamically constructed network to achieve accurate AVVE. First, we introduced a novel dynamically constructed deep learning framework, that evolves a single model into a bi-model volume estimation network. In this way, the EF correlation can be built directly based on the bi-model network. Second, we proposed an error correction strategy using dynamically created residual nodes, which is based on stochastic configurations with an EF correlation constraint. Finally, we formulated the proposed method into an end-to-end joint optimization framework for accurate ventricle volume estimation with effective error correction. Experiments and comparisons on large-scale cardiac magnetic resonance datasets were carried out. Results show that the proposed method outperforms state-of-the-art methods, and has good potential for clinical application. Besides, the proposed method is the first work to achieve error correction for AVVE and also has the potential to be extended to other medical index estimation tasks.
journal_name
Med Image Analjournal_title
Medical image analysisauthors
Luo G,Wang W,Tam C,Wang K,Cao S,Zhang H,Chen B,Li Sdoi
10.1016/j.media.2020.101723subject
Has Abstractpub_date
2020-08-01 00:00:00pages
101723eissn
1361-8415issn
1361-8423pii
S1361-8415(20)30087-6journal_volume
64pub_type
杂志文章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
更新日期：2017-01-01 00:00:00
abstract：:With the advent of large-scale imaging studies and big health data, and the corresponding growth in analytics, machine learning and computational image analysis methods, there are now exciting opportunities for deepening our understanding of the mechanisms and characteristics of heart disease. Two emerging fields are ...
journal_title：Medical image analysis
pub_type： 社论,评审
doi：10.1016/j.media.2016.06.027
更新日期：2016-10-01 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：: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
更新日期：2005-04-01 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：:Fast and accurate 2D/3D registration plays an important role in many applications, ranging from scientific and engineering domains all the way to medical care. Today's predominant methods are based on computationally expensive approaches, such as virtual forward or back projections, that limit the real-time applicabil...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101815
更新日期：2021-01-01 00:00:00
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
更新日期：2006-08-01 00:00:00
abstract：:A probabilistic framework for registering generalised point sets comprising multiple voxel-wise data features such as positions, orientations and scalar-valued quantities, is proposed. It is employed for the analysis of magnetic resonance diffusion tensor image (DTI)-derived quantities, such as fractional anisotropy (...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.01.001
更新日期：2019-04-01 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：: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：:An automated vendor-independent system for dose monitoring in computed tomography (CT) medical examinations involving ionizing radiation is presented in this paper. The system provides precise size-specific dose estimates (SSDE) following the American Association of Physicists in Medicine regulations. Our dose managem...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101898
更新日期：2021-02-01 00:00:00
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
更新日期：2016-10-01 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：: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
更新日期：2018-08-01 00:00:00
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
更新日期：2012-08-01 00:00:00
abstract：:Three-dimensional freehand ultrasound imaging produces a set of irregularly spaced B-scans, which are typically reconstructed on a regular grid for visualization and data analysis. Most standard reconstruction algorithms are designed to minimize computational requirements and do not exploit the underlying shape of the...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/s1361-8415(99)80028-0
更新日期：1999-12-01 00:00:00
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
更新日期：2009-06-01 00:00:00
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
更新日期：2014-10-01 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：: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：: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：: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
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：:Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many years. In the last decade, intensive developments in deep learning (DL) introduced new state-of-the-art segmentation systems. Despite outperforming the overall accuracy of existing systems, the effects of DL model proper...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101950
更新日期：2020-12-25 00:00:00
abstract：:Independent component analysis (ICA) is a statistical technique that estimates a set of sources mixed by an unknown mixing matrix using only a set of observations. For this purpose, the only assumption is that the sources are statistically independent. In many applications, some information about the nature of the unk...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2010.06.009
更新日期：2011-02-01 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：:Phase contrast, a noninvasive microscopy imaging technique, is widely used to capture time-lapse images to monitor the behavior of transparent cells without staining or altering them. Due to the optical principle, phase contrast microscopy images contain artifacts such as the halo and shade-off that hinder image segme...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2011.12.006
更新日期：2012-07-01 00:00:00
abstract：:In this paper, we propose a novel automated pipeline for extraction of sulcal fundi from triangulated cortical surfaces. This method consists of four consecutive steps. Firstly, we adopt a finite difference method to estimate principal curvatures, principal directions and curvature derivatives, along the principal dir...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2010.01.005
更新日期：2010-06-01 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：:This paper describes a new robust and fully automatic method for calibration of three-dimensional (3D) freehand ultrasound called Confhusius (CalibratiON for FreeHand UltraSound Imaging USage). 3D Freehand ultrasound consists in mounting a position sensor on a standard probe. The echographic B-scans can be localized i...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2004.06.021
更新日期：2005-02-01 00:00:00
