Quantitative analysis of multi-spectral fundus images.

Abstract:

:We have developed a new technique for extracting histological parameters from multi-spectral images of the ocular fundus. The new method uses a Monte Carlo simulation of the reflectance of the fundus to model how the spectral reflectance of the tissue varies with differing tissue histology. The model is parameterised by the concentrations of the five main absorbers found in the fundus: retinal haemoglobins, choroidal haemoglobins, choroidal melanin, RPE melanin and macular pigment. These parameters are shown to give rise to distinct variations in the tissue colouration. We use the results of the Monte Carlo simulations to construct an inverse model which maps tissue colouration onto the model parameters. This allows the concentration and distribution of the five main absorbers to be determined from suitable multi-spectral images. We propose the use of "image quotients" to allow this information to be extracted from uncalibrated image data. The filters used to acquire the images are selected to ensure a one-to-one mapping between model parameters and image quotients. To recover five model parameters uniquely, images must be acquired in six distinct spectral bands. Theoretical investigations suggest that retinal haemoglobins and macular pigment can be recovered with RMS errors of less than 10%. We present parametric maps showing the variation of these parameters across the posterior pole of the fundus. The results are in agreement with known tissue histology for normal healthy subjects. We also present an early result which suggests that, with further development, the technique could be used to successfully detect retinal haemorrhages.

journal_name

Med Image Anal

journal_title

Medical image analysis

authors

Styles IB,Calcagni A,Claridge E,Orihuela-Espina F,Gibson JM

doi

10.1016/j.media.2006.05.007

subject

Has Abstract

pub_date

2006-08-01 00:00:00

pages

578-97

issue

4

eissn

1361-8415

issn

1361-8423

pii

S1361-8415(06)00038-7

journal_volume

10

pub_type

杂志文章
  • Group-level cortical surface parcellation with sulcal pits labeling.

    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

    authors: Kaltenmark I,Deruelle C,Brun L,Lefèvre J,Coulon O,Auzias G

    更新日期:2020-12-01 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

  • 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

  • Hierarchical max-flow segmentation framework for multi-atlas segmentation with Kohonen self-organizing map based Gaussian mixture modeling.

    abstract::The incorporation of intensity, spatial, and topological information into large-scale multi-region segmentation has been a topic of ongoing research in medical image analysis. Multi-region segmentation problems, such as segmentation of brain structures, pose unique challenges in image segmentation in which regions may...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2015.05.005

    authors: Rajchl M,Baxter JS,McLeod AJ,Yuan J,Qiu W,Peters TM,Khan AR

    更新日期:2016-01-01 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

  • An efficient Riemannian statistical shape model using differential coordinates: With application to the classification of data from the Osteoarthritis Initiative.

    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

    authors: von Tycowicz C,Ambellan F,Mukhopadhyay A,Zachow S

    更新日期:2018-01-01 00:00:00

  • Ultrasound-fluoroscopy registration for prostate brachytherapy dosimetry.

    abstract::Prostate brachytherapy is a treatment for prostate cancer using radioactive seeds that are permanently implanted in the prostate. The treatment success depends on adequate coverage of the target gland with a therapeutic dose, while sparing the surrounding tissue. Since seed implantation is performed under transrectal ...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2012.06.001

    authors: Dehghan E,Lee J,Fallavollita P,Kuo N,Deguet A,Le Y,Clif Burdette E,Song DY,Prince JL,Fichtinger G

    更新日期:2012-10-01 00:00:00

  • Fusion of white and gray matter geometry: a framework for investigating brain development.

    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

    authors: Savadjiev P,Rathi Y,Bouix S,Smith AR,Schultz RT,Verma R,Westin CF

    更新日期:2014-12-01 00:00:00

  • Coupling of fluid and elastic models for biomechanical simulations of brain deformations using FEM.

    abstract::In order to improve the accuracy of image-guided neurosurgery, different biomechanical models have been developed to correct preoperative images with respect to intraoperative changes like brain shift or tumor resection. All existing biomechanical models simulate different anatomical structures by using either appropr...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/s1361-8415(02)00059-2

    authors: Hagemann A,Rohr K,Stiehl HS

    更新日期:2002-12-01 00:00:00

  • Intensity non-uniformity correction in MRI: existing methods and their validation.

    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

    authors: Belaroussi B,Milles J,Carme S,Zhu YM,Benoit-Cattin H

    更新日期:2006-04-01 00:00:00

  • Major depressive disorder identification by referenced multiset canonical correlation analysis with clinical scores.

    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

    authors: Lin W,Lv D,Han Z,Dong J,Yang L

    更新日期:2020-02-01 00:00:00

  • Adaptive, template moderated, spatially varying statistical classification.

    abstract::A novel image segmentation algorithm was developed to allow the automatic segmentation of both normal and abnormal anatomy from medical images. The new algorithm is a form of spatially varying statistical classification, in which an explicit anatomical template is used to moderate the segmentation obtained by statisti...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/s1361-8415(00)00003-7

    authors: Warfield SK,Kaus M,Jolesz FA,Kikinis R

    更新日期:2000-03-01 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

  • 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

  • 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

  • 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 addres...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2014.02.006

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

    更新日期:2014-05-01 00:00:00

  • Automated voxel-based 3D cortical thickness measurement in a combined Lagrangian-Eulerian PDE approach using partial volume maps.

    abstract::Accurate cortical thickness estimation is important for the study of many neurodegenerative diseases. Many approaches have been previously proposed, which can be broadly categorised as mesh-based and voxel-based. While the mesh-based approaches can potentially achieve subvoxel resolution, they usually lack the computa...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2009.07.003

    authors: Acosta O,Bourgeat P,Zuluaga MA,Fripp J,Salvado O,Ourselin S,Alzheimer's Disease Neuroimaging Initiative.

    更新日期:2009-10-01 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

  • Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images.

    abstract::This paper describes a method for the enhancement of curvilinear structures such as vessels and bronchi in three-dimensional (3-D) medical images. A 3-D line enhancement filter is developed with the aim of discriminating line structures from other structures and recovering line structures of various widths. The 3-D li...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/s1361-8415(98)80009-1

    authors: Sato Y,Nakajima S,Shiraga N,Atsumi H,Yoshida S,Koller T,Gerig G,Kikinis R

    更新日期:1998-06-01 00:00:00

  • Automatic detection of over 100 anatomical landmarks in medical CT images: A framework with independent detectors and combinatorial optimization.

    abstract::An automatic detection method for 197 anatomically defined landmarks in computed tomography (CT) volumes is presented. The proposed method can handle missed landmarks caused by detection failure, a limited imaging range and other problems using a novel combinatorial optimization framework with a two-stage sampling alg...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2016.04.001

    authors: Hanaoka S,Shimizu A,Nemoto M,Nomura Y,Miki S,Yoshikawa T,Hayashi N,Ohtomo K,Masutani Y

    更新日期:2017-01-01 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

  • Unmixing dynamic PET images with variable specific binding kinetics.

    abstract::To analyze dynamic positron emission tomography (PET) images, various generic multivariate data analysis techniques have been considered in the literature, such as principal component analysis (PCA), independent component analysis (ICA), factor analysis and nonnegative matrix factorization (NMF). Nevertheless, these c...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2018.07.011

    authors: Cavalcanti YC,Oberlin T,Dobigeon N,Stute S,Ribeiro M,Tauber C

    更新日期:2018-10-01 00:00:00

  • Groupwise registration with global-local graph shrinkage in atlas construction.

    abstract::Graph-based groupwise registration methods are widely used in atlas construction. Given a group of images, a graph is built whose nodes represent the images, and whose edges represent a geodesic path between two nodes. The distribution of images on an image manifold is explored through edge traversal in a graph. The f...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2020.101711

    authors: Fu T,Yang J,Li Q,Ai D,Song H,Jiang Y,Wang Y,Frangi AF

    更新日期:2020-08-01 00:00:00

  • Personalized mitral valve closure computation and uncertainty analysis from 3D echocardiography.

    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

    authors: Grbic S,Easley TF,Mansi T,Bloodworth CH,Pierce EL,Voigt I,Neumann D,Krebs J,Yuh DD,Jensen MO,Comaniciu D,Yoganathan AP

    更新日期:2017-01-01 00:00:00

  • Symmetric positive semi-definite Cartesian Tensor fiber orientation distributions (CT-FOD).

    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

    authors: Weldeselassie YT,Barmpoutis A,Atkins MS

    更新日期:2012-08-01 00:00:00

  • Noise reduction in diffusion MRI using non-local self-similar information in joint x-q space.

    abstract::Diffusion MRI affords valuable insights into white matter microstructures, but suffers from low signal-to-noise ratio (SNR), especially at high diffusion weighting (i.e., b-value). To avoid time-intensive repeated acquisition, post-processing algorithms are often used to reduce noise. Among existing methods, non-local...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2019.01.006

    authors: Chen G,Wu Y,Shen D,Yap PT

    更新日期:2019-04-01 00:00:00

  • Hierarchical segmentation using equivalence test (HiSET): Application to DCE image sequences.

    abstract::Dynamical contrast enhanced (DCE) imaging allows non invasive access to tissue micro-vascularization. It appears as a promising tool to build imaging biomarkers for diagnostic, prognosis or anti-angiogenesis treatment monitoring of cancer. However, quantitative analysis of DCE image sequences suffers from low signal t...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2018.10.007

    authors: Liu F,Cuenod CA,Thomassin-Naggara I,Chemouny S,Rozenholc Y

    更新日期:2019-01-01 00:00:00

  • Efficient multi-modal dense field non-rigid registration: alignment of histological and section images.

    abstract::We describe a new algorithm for non-rigid registration capable of estimating a constrained dense displacement field from multi-modal image data. We applied this algorithm to capture non-rigid deformation between digital images of histological slides and digital flat-bed scanned images of cryotomed sections of the lary...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2005.04.003

    authors: du Bois d'Aische A,Craene MD,Geets X,Gregoire V,Macq B,Warfield SK

    更新日期:2005-12-01 00:00:00

  • Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge.

    abstract::Knowledge of whole heart anatomy is a prerequisite for many clinical applications. Whole heart segmentation (WHS), which delineates substructures of the heart, can be very valuable for modeling and analysis of the anatomy and functions of the heart. However, automating this segmentation can be challenging due to the l...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2019.101537

    authors: Zhuang X,Li L,Payer C,Štern D,Urschler M,Heinrich MP,Oster J,Wang C,Smedby Ö,Bian C,Yang X,Heng PA,Mortazi A,Bagci U,Yang G,Sun C,Galisot G,Ramel JY,Brouard T,Tong Q,Si W,Liao X,Zeng G,Shi Z,Zheng G,Wang

    更新日期:2019-12-01 00:00:00

  • Automated localization of breast cancer in DCE-MRI.

    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

    authors: Gubern-Mérida A,Martí R,Melendez J,Hauth JL,Mann RM,Karssemeijer N,Platel B

    更新日期:2015-02-01 00:00:00