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); compact clusters indicate good registration. This method iteratively fits the JISP clusters with regressors (in the form of points and line segments), and uses those regressors to efficiently compute the next motion increment. The result is a striking, dynamic process in which the regressors float around the JISP, tracking groups of points as they contract into tight clusters. One of the method's strengths is that it is intuitive and customizable, offering a multitude of ways to incorporate prior knowledge to guide the registration process. Moreover, the method is adaptive, and can adjust itself to fit data that does not quite match the prior model. Finally, the method is efficiently expandable to higher-dimensional scatter plots, avoiding the "curse of dimensionality" inherent in histogram-based registration methods such as MI and NMI. In two sets of experiments, a simple implementation of the new registration framework is shown to be comparable to (if not superior to) state-of-the-art implementations of NMI and CR in both accuracy and convergence robustness.
journal_name
Med Image Analjournal_title
Medical image analysisauthors
Orchard Jdoi
10.1016/j.media.2007.12.002subject
Has Abstractpub_date
2008-08-01 00:00:00pages
385-96issue
4eissn
1361-8415issn
1361-8423pii
S1361-8415(08)00005-4journal_volume
12pub_type
杂志文章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
更新日期：2019-07-01 00:00:00
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
更新日期：2006-04-01 00:00:00
abstract：:We describe a new 3-D statistical shape model of the heart consisting of atria, ventricles and epicardium. The model was constructed by combining information on standard short- and long-axis cardiac MR images. In the model, the variability of the shape was modeled with PCA- and ICA-based shape models as well as with n...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2004.06.013
更新日期：2004-09-01 00:00:00
abstract：:In this paper, we present a generative Bayesian approach for estimating the low-dimensional latent space of diffeomorphic shape variability in a population of images. We develop a latent variable model for principal geodesic analysis (PGA) that provides a probabilistic framework for factor analysis in the space of dif...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2015.04.009
更新日期：2015-10-01 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：:We propose a novel airway segmentation method in volumetric chest computed tomography (CT) and evaluate its performance on multiple datasets. The segmentation is performed voxel-by-voxel by a 2.5D convolutional neural net (2.5D CNN) trained in a supervised manner. To enhance the accuracy of the segmented airway tree, ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2018.10.006
更新日期：2019-01-01 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：: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：: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：: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：: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：: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：: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：:We describe a system for respiratory motion correction of MRI-derived roadmaps for use in X-ray guided cardiac catheterisation procedures. The technique uses a subject-specific affine motion model that is quickly constructed from a short pre-procedure MRI scan. We test a dynamic MRI sequence that acquires a small numb...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2009.01.003
更新日期：2009-06-01 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：: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：: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
更新日期：2005-12-01 00:00:00
abstract：:The current standard of care for glaucoma patients consists of functional assessment of vision via visual field (VF) testing, which is sensitive but subjective, time-consuming, and often unreliable. A new imaging technology, Fourier domain optical coherence tomography (OCT), is being introduced to assess the structura...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2011.05.012
更新日期：2012-01-01 00:00:00
abstract：:The eye affords a unique opportunity to inspect a rich part of the human microvasculature non-invasively via retinal imaging. Retinal blood vessel segmentation and classification are prime steps for the diagnosis and risk assessment of microvascular and systemic diseases. A high volume of techniques based on deep lear...
journal_title：Medical image analysis
pub_type： 杂志文章,评审
doi：10.1016/j.media.2020.101905
更新日期：2021-02-01 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：:Due to the development of deep learning, an increasing number of research works have been proposed to establish automated analysis systems for 3D volumetric medical data to improve the quality of patient care. However, it is challenging to obtain a large number of annotated 3D medical data needed to train a neural net...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101746
更新日期：2020-08-01 00:00:00
abstract：:This paper presents a new hybrid camera motion tracking method for bronchoscopic navigation combining SIFT, epipolar geometry analysis, Kalman filtering, and image registration. In a thorough evaluation, we compare it to state-of-the-art tracking methods. Our hybrid algorithm for predicting bronchoscope motion uses SI...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2010.11.001
更新日期：2012-04-01 00:00:00
abstract：:The automatic extraction of blood vessels in non-fluorescein eye fundus images is a tough task in applications such as diabetic retinopathy screening. However, vessel shapes have complex variations, and accurate modeling of retinal vascular structures is challenging. We have therefore developed a new approach to accur...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2015.09.002
更新日期：2015-12-01 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：:Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is increasingly being used for the detection and diagnosis of breast cancer. Compared to mammography, DCE-MRI provides higher sensitivity, however its specificity is variable. Moreover, DCE-MRI data analysis is time consuming and depends on reader expertis...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2014.12.001
更新日期：2015-02-01 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：: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：: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：: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
更新日期：2021-02-01 00:00:00
