PCA-based groupwise image registration for quantitative MRI.

Abstract:

:Quantitative magnetic resonance imaging (qMRI) is a technique for estimating quantitative tissue properties, such as the T1 and T2 relaxation times, apparent diffusion coefficient (ADC), and various perfusion measures. This estimation is achieved by acquiring multiple images with different acquisition parameters (or at multiple time points after injection of a contrast agent) and by fitting a qMRI signal model to the image intensities. Image registration is often necessary to compensate for misalignments due to subject motion and/or geometric distortions caused by the acquisition. However, large differences in image appearance make accurate image registration challenging. In this work, we propose a groupwise image registration method for compensating misalignment in qMRI. The groupwise formulation of the method eliminates the requirement of choosing a reference image, thus avoiding a registration bias. The method minimizes a cost function that is based on principal component analysis (PCA), exploiting the fact that intensity changes in qMRI can be described by a low-dimensional signal model, but not requiring knowledge on the specific acquisition model. The method was evaluated on 4D CT data of the lungs, and both real and synthetic images of five different qMRI applications: T1 mapping in a porcine heart, combined T1 and T2 mapping in carotid arteries, ADC mapping in the abdomen, diffusion tensor mapping in the brain, and dynamic contrast-enhanced mapping in the abdomen. Each application is based on a different acquisition model. The method is compared to a mutual information-based pairwise registration method and four other state-of-the-art groupwise registration methods. Registration accuracy is evaluated in terms of the precision of the estimated qMRI parameters, overlap of segmented structures, distance between corresponding landmarks, and smoothness of the deformation. In all qMRI applications the proposed method performed better than or equally well as competing methods, while avoiding the need to choose a reference image. It is also shown that the results of the conventional pairwise approach do depend on the choice of this reference image. We therefore conclude that our groupwise registration method with a similarity measure based on PCA is the preferred technique for compensating misalignments in qMRI.

journal_name

Med Image Anal

journal_title

Medical image analysis

authors

Huizinga W,Poot DH,Guyader JM,Klaassen R,Coolen BF,van Kranenburg M,van Geuns RJ,Uitterdijk A,Polfliet M,Vandemeulebroucke J,Leemans A,Niessen WJ,Klein S

doi

10.1016/j.media.2015.12.004

subject

Has Abstract

pub_date

2016-04-01 00:00:00

pages

65-78

eissn

1361-8415

issn

1361-8423

pii

S1361-8415(15)00185-1

journal_volume

29

pub_type

杂志文章
  • 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

  • Development and comparison of new hybrid motion tracking for bronchoscopic navigation.

    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

    authors: Luó X,Feuerstein M,Deguchi D,Kitasaka T,Takabatake H,Mori K

    更新日期:2012-04-01 00:00:00

  • Automated size-specific dose estimates using deep learning image processing.

    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

    authors: Juszczyk J,Badura P,Czajkowska J,Wijata A,Andrzejewski J,Bozek P,Smolinski M,Biesok M,Sage A,Rudzki M,Wieclawek W

    更新日期:2021-02-01 00:00:00

  • Reducing annotation effort in digital pathology: A Co-Representation learning framework for classification tasks.

    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

    authors: Pati P,Foncubierta-Rodríguez A,Goksel O,Gabrani M

    更新日期:2021-01-01 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

  • Image guidance in orthopaedics and traumatology: A historical perspective.

    abstract::In this note we summarize the history of computer aided surgery in orthopaedics and traumatology from the end of the nineteenth century to currently observable future trends. We concentrate on the two major components of such systems, pre-operative planning and intra-operative execution. The evolution of the necessary...

    journal_title:Medical image analysis

    pub_type: 社论

    doi:10.1016/j.media.2016.06.033

    authors: Székely G,Nolte LP

    更新日期:2016-10-01 00:00:00

  • Simulation of cardiac pathologies using an electromechanical biventricular model and XMR interventional imaging.

    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

    authors: Sermesant M,Rhode K,Sanchez-Ortiz GI,Camara O,Andriantsimiavona R,Hegde S,Rueckert D,Lambiase P,Bucknall C,Rosenthal E,Delingette H,Hill DL,Ayache N,Razavi R

    更新日期:2005-10-01 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

  • Analytical and fast Fiber Orientation Distribution reconstruction in 3D-Polarized Light Imaging.

    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

    authors: Alimi A,Deslauriers-Gauthier S,Matuschke F,Müller A,Muenzing SEA,Axer M,Deriche R

    更新日期:2020-10-01 00:00:00

  • A variational framework for integrating segmentation and registration through active contours.

    abstract::Traditionally, segmentation and registration have been solved as two independent problems, even though it is often the case that the solution to one impacts the solution to the other. In this paper, we introduce a geometric, variational framework that uses active contours to simultaneously segment and register feature...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/s1361-8415(03)00004-5

    authors: Yezzi A,Zöllei L,Kapur T

    更新日期:2003-06-01 00:00:00

  • Computerized detection of pulmonary nodules in chest radiographs based on morphological features and wavelet snake model.

    abstract::We have developed a new computer-aided diagnosis scheme for automated detection of lung nodules in digital chest radiographs based on a combination of morphological features and the wavelet snake. In our scheme, two processes were applied in parallel to reduce the false-positive detections after initial nodule candida...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/s1361-8415(02)00064-6

    authors: Keserci B,Yoshida H

    更新日期:2002-12-01 00:00:00

  • Regularized siamese neural network for unsupervised outlier detection on brain multiparametric magnetic resonance imaging: Application to epilepsy lesion screening.

    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

    authors: Alaverdyan Z,Jung J,Bouet R,Lartizien C

    更新日期:2020-02-01 00:00:00

  • Discriminant snakes for 3D reconstruction of anatomical organs.

    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

    authors: Pardo XM,Radeva P,Cabello D

    更新日期:2003-09-01 00:00:00

  • 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

  • Luminosity and contrast normalization in retinal images.

    abstract::Retinal images are routinely acquired and assessed to provide diagnostic evidence for many important diseases, e.g. diabetes or hypertension. Because of the acquisition process, very often these images are non-uniformly illuminated and exhibit local luminosity and contrast variability. This problem may seriously affec...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2004.07.001

    authors: Foracchia M,Grisan E,Ruggeri A

    更新日期:2005-06-01 00:00:00

  • Pseudo-healthy synthesis with pathology disentanglement and adversarial learning.

    abstract::Pseudo-healthy synthesis is the task of creating a subject-specific 'healthy' image from a pathological one. Such images can be helpful in tasks such as anomaly detection and understanding changes induced by pathology and disease. In this paper, we present a model that is encouraged to disentangle the information of p...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2020.101719

    authors: Xia T,Chartsias A,Tsaftaris SA

    更新日期:2020-08-01 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

  • Multimodal image registration using floating regressors in the joint intensity scatter plot.

    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

    authors: Orchard J

    更新日期:2008-08-01 00:00:00

  • Clavicle segmentation in chest radiographs.

    abstract::Automated delineation of anatomical structures in chest radiographs is difficult due to superimposition of multiple structures. In this work an automated technique to segment the clavicles in posterior-anterior chest radiographs is presented in which three methods are combined. Pixel classification is applied in two s...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2012.06.009

    authors: Hogeweg L,Sánchez CI,de Jong PA,Maduskar P,van Ginneken B

    更新日期:2012-12-01 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

  • Large deformation diffeomorphic registration of diffusion-weighted imaging data.

    abstract::Registration plays an important role in group analysis of diffusion-weighted imaging (DWI) data. It can be used to build a reference anatomy for investigating structural variation or tracking changes in white matter. Unlike traditional scalar image registration where spatial alignment is the only focus, registration o...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2014.06.012

    authors: Zhang P,Niethammer M,Shen D,Yap PT

    更新日期:2014-12-01 00:00:00

  • An accurate, fast and robust method to generate patient-specific cubic Hermite meshes.

    abstract::In-silico continuum simulations of organ and tissue scale physiology often require a discretisation or mesh of the solution domain. Cubic Hermite meshes provide a smooth representation of anatomy that is well-suited for simulating large deformation mechanics. Models of organ mechanics and deformation have demonstrated...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2011.06.010

    authors: Lamata P,Niederer S,Nordsletten D,Barber DC,Roy I,Hose DR,Smith N

    更新日期:2011-12-01 00:00:00

  • Segmentation of pulmonary nodules of various densities with morphological approaches and convexity models.

    abstract::Accurate segmentation of a pulmonary nodule is an important and active area of research in medical image processing. Although many algorithms have been reported in literature for this problem, those that are applicable to various density types have not been available until recently. In this paper, we propose a new alg...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2010.08.005

    authors: Kubota T,Jerebko AK,Dewan M,Salganicoff M,Krishnan A

    更新日期:2011-02-01 00:00:00

  • Stochastic finite element framework for simultaneous estimation of cardiac kinematic functions and material parameters.

    abstract::A stochastic finite element framework is presented for the simultaneous estimation of the cardiac kinematic functions and material model parameters from periodic medical image sequences. While existing biomechanics studies of the myocardial material constitutive laws have assumed known tissue kinematic measurements, a...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/s1361-8415(03)00066-5

    authors: Shi P,Liu H

    更新日期:2003-12-01 00:00:00

  • Characterization of task-free and task-performance brain states via functional connectome patterns.

    abstract::Both resting state fMRI (R-fMRI) and task-based fMRI (T-fMRI) have been widely used to study the functional activities of the human brain during task-free and task-performance periods, respectively. However, due to the difficulty in strictly controlling the participating subject's mental status and their cognitive beh...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2013.07.003

    authors: Zhang X,Guo L,Li X,Zhang T,Zhu D,Li K,Chen H,Lv J,Jin C,Zhao Q,Li L,Liu T

    更新日期:2013-12-01 00:00:00

  • Accurate estimation of retinal vessel width using bagged decision trees and an extended multiresolution Hermite model.

    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

    authors: Lupaşcu CA,Tegolo D,Trucco E

    更新日期:2013-12-01 00:00:00

  • Predicting the progression of mild cognitive impairment using machine learning: A systematic, quantitative and critical review.

    abstract::We performed a systematic review of studies focusing on the automatic prediction of the progression of mild cognitive impairment to Alzheimer's disease (AD) dementia, and a quantitative analysis of the methodological choices impacting performance. This review included 172 articles, from which 234 experiments were extr...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2020.101848

    authors: Ansart M,Epelbaum S,Bassignana G,Bône A,Bottani S,Cattai T,Couronné R,Faouzi J,Koval I,Louis M,Thibeau-Sutre E,Wen J,Wild A,Burgos N,Dormont D,Colliot O,Durrleman S

    更新日期:2021-01-01 00:00:00

  • Shape regression machine and efficient segmentation of left ventricle endocardium from 2D B-mode echocardiogram.

    abstract::We present a machine learning approach called shape regression machine (SRM) for efficient segmentation of an anatomic structure that exhibits a deformable shape in a medical image, e.g., left ventricle endocardial wall in an echocardiogram. The SRM achieves efficient segmentation via statistical learning of the inter...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2010.04.002

    authors: Zhou SK

    更新日期:2010-08-01 00:00:00

  • A novel deformation method for fast simulation of biological tissue formed by fibers and fluid.

    abstract::This paper presents a new approach to the simulation of soft tissues deformation suitable for real time computation, particularly intriguing for medical applications. The approach implements a quasi-static solution for elastic global deformations of objects filled with fluid and fibers, which can be a good approximati...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2012.04.002

    authors: Costa IF

    更新日期:2012-07-01 00:00:00

  • Statistical shape model of atria, ventricles and epicardium from short- and long-axis MR images.

    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

    authors: Lötjönen J,Kivistö S,Koikkalainen J,Smutek D,Lauerma K

    更新日期:2004-09-01 00:00:00