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 addressed based on pattern classification techniques, while registration is performed by maximizing the similarity between volumes and is modular with respect to the matching criterion. The two problems are coupled by relaxing the registration term in the tumor area, corresponding to areas of high classification score and high dissimilarity between volumes. In order to overcome the main shortcomings of discrete approaches regarding appropriate sampling of the solution space as well as important memory requirements, content driven samplings of the discrete displacement set and the sparse grid are considered, based on the local segmentation and registration uncertainties recovered by the min marginal energies. State of the art results on a substantial low-grade glioma database demonstrate the potential of our method, while our proposed approach shows maintained performance and strongly reduced complexity of the model.

journal_name

Med Image Anal

journal_title

Medical image analysis

authors

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

doi

10.1016/j.media.2014.02.006

subject

Has Abstract

pub_date

2014-05-01 00:00:00

pages

647-59

issue

4

eissn

1361-8415

issn

1361-8423

pii

S1361-8415(14)00029-2

journal_volume

18

pub_type

杂志文章
  • Manifold modeling for brain population analysis.

    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

    authors: Gerber S,Tasdizen T,Thomas Fletcher P,Joshi S,Whitaker R,Alzheimers Disease Neuroimaging Initiative (ADNI).

    更新日期:2010-10-01 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

  • Rubik's Cube+: A self-supervised feature learning framework for 3D medical image analysis.

    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

    authors: Zhu J,Li Y,Hu Y,Ma K,Zhou SK,Zheng Y

    更新日期:2020-08-01 00:00:00

  • Intrasubject multimodal groupwise registration with the conditional template entropy.

    abstract::Image registration is an important task in medical image analysis. Whereas most methods are designed for the registration of two images (pairwise registration), there is an increasing interest in simultaneously aligning more than two images using groupwise registration. Multimodal registration in a groupwise setting r...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2018.02.003

    authors: Polfliet M,Klein S,Huizinga W,Paulides MM,Niessen WJ,Vandemeulebroucke J

    更新日期:2018-05-01 00:00:00

  • Global localization of 3D anatomical structures by pre-filtered Hough forests and discrete optimization.

    abstract::The accurate localization of anatomical landmarks is a challenging task, often solved by domain specific approaches. We propose a method for the automatic localization of landmarks in complex, repetitive anatomical structures. The key idea is to combine three steps: (1) a classifier for pre-filtering anatomical landma...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2013.02.004

    authors: Donner R,Menze BH,Bischof H,Langs G

    更新日期:2013-12-01 00:00:00

  • Identifying Cross-individual Correspondences of 3-hinge Gyri.

    abstract::Human brain alignment based on imaging data has long been an intriguing research topic. One of the challenges is the huge inter-individual variabilities, which are pronounced not only in cortical folding patterns, but also in the underlying structural and functional patterns. Also, it is still not fully understood how...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2020.101700

    authors: Zhang T,Huang Y,Zhao L,He Z,Jiang X,Guo L,Hu X,Liu T

    更新日期:2020-07-01 00:00:00

  • A spatiotemporal statistical atlas of motion for the quantification of abnormal myocardial tissue velocities.

    abstract::In this paper, we present a new method for the automatic comparison of myocardial motion patterns and the characterization of their degree of abnormality, based on a statistical atlas of motion built from a reference healthy population. Our main contribution is the computation of atlas-based indexes that quantify the ...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2010.12.006

    authors: Duchateau N,De Craene M,Piella G,Silva E,Doltra A,Sitges M,Bijnens BH,Frangi AF

    更新日期:2011-06-01 00:00:00

  • Recovering from missing data in population imaging - Cardiac MR image imputation via conditional generative adversarial nets.

    abstract::Accurate ventricular volume measurements are the primary indicators of normal/abnor- mal cardiac function and are dependent on the Cardiac Magnetic Resonance (CMR) volumes being complete. However, missing or unusable slices owing to the presence of image artefacts such as respiratory or motion ghosting, aliasing, ring...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2020.101812

    authors: Xia Y,Zhang L,Ravikumar N,Attar R,Piechnik SK,Neubauer S,Petersen SE,Frangi AF

    更新日期:2021-01-01 00:00:00

  • Coupled parametric model for estimation of visual field tests based on OCT macular thickness maps, and vice versa, in glaucoma care.

    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

    authors: Tsai A,Caprioli J,Shen LQ

    更新日期:2012-01-01 00:00:00

  • A review of machine learning methods for retinal blood vessel segmentation and artery/vein classification.

    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

    authors: Mookiah MRK,Hogg S,MacGillivray TJ,Prathiba V,Pradeepa R,Mohan V,Anjana RM,Doney AS,Palmer CNA,Trucco E

    更新日期:2021-02-01 00:00:00

  • SDAE-GAN: Enable high-dimensional pathological images in liver cancer survival prediction with a policy gradient based data augmentation method.

    abstract::High-dimensional pathological images produced by Immunohistochemistry (IHC) methods consist of many pathological indexes, which play critical roles in cancer treatment planning. However, these indexes currently cannot be utilized in survival prediction because joining them with patients' clinicopathological features (...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2020.101640

    authors: Wu H,Gao R,Sheng YP,Chen B,Li S

    更新日期:2020-05-01 00:00:00

  • Robust registration procedures for endoscopic imaging.

    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

    authors: Konen W,Tombrock S,Scholz M

    更新日期:2007-12-01 00:00:00

  • CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation.

    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

    authors: Kavur AE,Gezer NS,Barış M,Aslan S,Conze PH,Groza V,Pham DD,Chatterjee S,Ernst P,Özkan S,Baydar B,Lachinov D,Han S,Pauli J,Isensee F,Perkonigg M,Sathish R,Rajan R,Sheet D,Dovletov G,Speck O,Nürnberger A,Maier-H

    更新日期:2020-12-25 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

  • 4D hyperspherical harmonic (HyperSPHARM) representation of surface anatomy: a holistic treatment of multiple disconnected anatomical structures.

    abstract::Image-based parcellation of the brain often leads to multiple disconnected anatomical structures, which pose significant challenges for analyses of morphological shapes. Existing shape models, such as the widely used spherical harmonic (SPHARM) representation, assume topological invariance, so are unable to simultaneo...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2015.02.004

    authors: Pasha Hosseinbor A,Chung MK,Koay CG,Schaefer SM,van Reekum CM,Schmitz LP,Sutterer M,Alexander AL,Davidson RJ

    更新日期:2015-05-01 00:00:00

  • Hierarchical spherical deformation for cortical surface registration.

    abstract::We present hierarchical spherical deformation for a group-wise shape correspondence to address template selection bias and to minimize registration distortion. In this work, we aim at a continuous and smooth deformation field to guide accurate cortical surface registration. In conventional spherical registration metho...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2019.06.013

    authors: Lyu I,Kang H,Woodward ND,Styner MA,Landman BA

    更新日期:2019-10-01 00:00:00

  • Spatially variable Rician noise in magnetic resonance imaging.

    abstract::Magnetic resonance images tend to be influenced by various random factors usually referred to as "noise". The principal sources of noise and related artefacts can be divided into two types: arising from hardware (acquisition coil arrays, gradient coils, field inhomogeneity); and arising from the subject (physiological...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2011.12.002

    authors: Maximov II,Farrher E,Grinberg F,Shah NJ

    更新日期:2012-02-01 00:00:00

  • An improved deep network for tissue microstructure estimation with uncertainty quantification.

    abstract::Deep learning based methods have improved the estimation of tissue microstructure from diffusion magnetic resonance imaging (dMRI) scans acquired with a reduced number of diffusion gradients. These methods learn the mapping from diffusion signals in a voxel or patch to tissue microstructure measures. In particular, it...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2020.101650

    authors: Ye C,Li Y,Zeng X

    更新日期:2020-04-01 00:00:00

  • Improvement of fully automated airway segmentation on volumetric computed tomographic images using a 2.5 dimensional convolutional neural net.

    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

    authors: Yun J,Park J,Yu D,Yi J,Lee M,Park HJ,Lee JG,Seo JB,Kim N

    更新日期:2019-01-01 00:00:00

  • Nonlinear multiscale regularisation in MR elastography: Towards fine feature mapping.

    abstract::Fine-featured elastograms may provide additional information of radiological interest in the context of in vivo elastography. Here a new image processing pipeline called ESP (Elastography Software Pipeline) is developed to create Magnetic Resonance Elastography (MRE) maps of viscoelastic parameters (complex modulus ma...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2016.05.012

    authors: Barnhill E,Hollis L,Sack I,Braun J,Hoskins PR,Pankaj P,Brown C,van Beek EJR,Roberts N

    更新日期:2017-01-01 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

  • 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

  • Segmentation of carpal bones from CT images using skeletally coupled deformable models.

    abstract::The in vivo investigation of joint kinematics in normal and injured wrist requires the segmentation of carpal bones from 3D (CT) images, and their registration over time. The non-uniformity of bone tissue, ranging from dense cortical bone to textured spongy bone, the irregular shape of closely packed carpal bones, sma...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/s1361-8415(02)00065-8

    authors: Sebastian TB,Tek H,Crisco JJ,Kimia BB

    更新日期:2003-03-01 00:00:00

  • Ultrasonic and elasticity imaging to model disease-induced changes in soft-tissue structure.

    abstract::Ultrasonic techniques are presented for the study of soft biological tissue structure and function. Changes in echo waveforms caused by microscopic variations in the mechanical properties of tissue can reveal disease mechanism, in vivo. On a larger scale, elasticity imaging describes the macroscopic mechanical propert...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/s1361-8415(98)80014-5

    authors: Chaturvedi P,Insana MF,Hall TJ

    更新日期:1998-12-01 00:00:00

  • Segmentation of lumen and outer wall of abdominal aortic aneurysms from 3D black-blood MRI with a registration based geodesic active contour model.

    abstract::Segmentation of the geometric morphology of abdominal aortic aneurysm is important for interventional planning. However, the segmentation of both the lumen and the outer wall of aneurysm in magnetic resonance (MR) image remains challenging. This study proposes a registration based segmentation methodology for efficien...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2017.05.005

    authors: Wang Y,Seguro F,Kao E,Zhang Y,Faraji F,Zhu C,Haraldsson H,Hope M,Saloner D,Liu J

    更新日期:2017-08-01 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

  • A symbolic environment for visualizing activated foci in functional neuroimaging datasets.

    abstract::This paper presents a symbolic visualization environment known as the Corner Cube environment, which was developed to facilitate rapid examination and comparison of activated foci defined by analyses of functional neuroimaging datasets. We have performed a comparative evaluation of this environment against maximum-int...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/s1361-8415(98)80020-0

    authors: Rehm K,Lakshminaryan K,Frutiger S,Schaper KA,Sumners DW,Strother SC,Anderson JR,Rottenberg DA

    更新日期:1998-09-01 00:00:00

  • Exudate detection in color retinal images for mass screening of diabetic retinopathy.

    abstract::The automatic detection of exudates in color eye fundus images is an important task in applications such as diabetic retinopathy screening. The presented work has been undertaken in the framework of the TeleOphta project, whose main objective is to automatically detect normal exams in a tele-ophthalmology network, thu...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2014.05.004

    authors: Zhang X,Thibault G,Decencière E,Marcotegui B,Laÿ B,Danno R,Cazuguel G,Quellec G,Lamard M,Massin P,Chabouis A,Victor Z,Erginay A

    更新日期:2014-10-01 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

  • An image space approach to Cartesian based parallel MR imaging with total variation regularization.

    abstract::The Cartesian parallel magnetic imaging problem is formulated variationally using a high-order penalty for coil sensitivities and a total variation like penalty for the reconstructed image. Then the optimality system is derived and numerically discretized. The objective function used is non-convex, but it possesses a ...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2011.07.002

    authors: Keeling SL,Clason C,Hintermüller M,Knoll F,Laurain A,von Winckel G

    更新日期:2012-01-01 00:00:00