A procedure to average 3D anatomical structures.

Abstract:

:Creating a feature-preserving average of three dimensional anatomical surfaces extracted from volume image data is a complex task. Unlike individual images, averages present right-left symmetry and smooth surfaces which give insight into typical proportions. Averaging multiple biological surface images requires careful superimposition and sampling of homologous regions. Our approach to biological surface image averaging grows out of a wireframe surface tessellation approach by Cutting et al. (1993). The surface delineating wires represent high curvature crestlines. By adding tile boundaries in flatter areas the 3D image surface is parametrized into anatomically labeled (homology mapped) grids. We extend the Cutting et al. wireframe approach by encoding the entire surface as a series of B-spline space curves. The crestline averaging algorithm developed by Cutting et al. may then be used for the entire surface. Shape preserving averaging of multiple surfaces requires careful positioning of homologous surface regions such as these B-spline space curves. We test the precision of this new procedure and its ability to appropriately position groups of surfaces in order to produce a shape-preserving average. Our result provides an average that well represents the source images and may be useful clinically as a deformable model or for animation.

journal_name

Med Image Anal

journal_title

Medical image analysis

authors

Subramanya K,Dean D

doi

10.1016/s1361-8415(00)00031-1

subject

Has Abstract

pub_date

2000-12-01 00:00:00

pages

317-34

issue

4

eissn

1361-8415

issn

1361-8423

pii

S1361841500000311

journal_volume

4

pub_type

杂志文章
  • Computer aided diagnosis of thyroid nodules based on the devised small-datasets multi-view ensemble learning.

    abstract::With the development of deep learning, its application in diagnosis of benign and malignant thyroid nodules has been widely concerned. However, it is difficult to obtain medical images, resulting in insufficient number of data, which contradicts the large amount of data required for acquiring effective deep learning d...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2020.101819

    authors: Chen Y,Li D,Zhang X,Jin J,Shen Y

    更新日期:2021-01-01 00:00:00

  • Interactive training system for interventional electrocardiology procedures.

    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

    authors: Talbot H,Spadoni F,Duriez C,Sermesant M,O'Neill M,Jaïs P,Cotin S,Delingette H

    更新日期:2017-01-01 00:00:00

  • Confhusius: a robust and fully automatic calibration method for 3D freehand ultrasound.

    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

    authors: Rousseau F,Hellier P,Barillot C

    更新日期:2005-02-01 00:00:00

  • IDRiD: Diabetic Retinopathy - Segmentation and Grading Challenge.

    abstract::Diabetic Retinopathy (DR) is the most common cause of avoidable vision loss, predominantly affecting the working-age population across the globe. Screening for DR, coupled with timely consultation and treatment, is a globally trusted policy to avoid vision loss. However, implementation of DR screening programs is chal...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2019.101561

    authors: Porwal P,Pachade S,Kokare M,Deshmukh G,Son J,Bae W,Liu L,Wang J,Liu X,Gao L,Wu T,Xiao J,Wang F,Yin B,Wang Y,Danala G,He L,Choi YH,Lee YC,Jung SH,Li Z,Sui X,Wu J,Li X,Zhou T,Toth J,Baran A,Kori A,Ch

    更新日期:2020-01-01 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

  • 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

  • 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

  • Automated comprehensive Adolescent Idiopathic Scoliosis assessment using MVC-Net.

    abstract::Automated quantitative estimation of spinal curvature is an important task for the ongoing evaluation and treatment planning of Adolescent Idiopathic Scoliosis (AIS). It solves the widely accepted disadvantage of manual Cobb angle measurement (time-consuming and unreliable) which is currently the gold standard for AIS...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2018.05.005

    authors: Wu H,Bailey C,Rasoulinejad P,Li S

    更新日期:2018-08-01 00:00:00

  • Abdominal multi-organ segmentation with organ-attention networks and statistical fusion.

    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

    authors: Wang Y,Zhou Y,Shen W,Park S,Fishman EK,Yuille AL

    更新日期:2019-07-01 00:00:00

  • Objective and expert-independent validation of retinal image registration algorithms by a projective imaging distortion model.

    abstract::Fundus camera imaging of the retina is widely used to diagnose and manage ophthalmologic disorders including diabetic retinopathy, glaucoma, and age-related macular degeneration. Retinal images typically have a limited field of view, and multiple images can be joined together using an image registration technique to f...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2010.04.001

    authors: Lee S,Reinhardt JM,Cattin PC,Abràmoff MD

    更新日期:2010-08-01 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

  • 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

  • Explainable cardiac pathology classification on cine MRI with motion characterization by semi-supervised learning of apparent flow.

    abstract::We propose a method to classify cardiac pathology based on a novel approach to extract image derived features to characterize the shape and motion of the heart. An original semi-supervised learning procedure, which makes efficient use of a large amount of non-segmented images and a small amount of images segmented man...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2019.06.001

    authors: Zheng Q,Delingette H,Ayache N

    更新日期:2019-08-01 00:00:00

  • Automatic segmentation of 3D micro-CT coronary vascular images.

    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

    authors: Lee J,Beighley P,Ritman E,Smith N

    更新日期:2007-12-01 00:00:00

  • Multiple hypothesis template tracking of small 3D vessel structures.

    abstract::A multiple hypothesis tracking approach to the segmentation of small 3D vessel structures is presented. By simultaneously tracking multiple hypothetical vessel trajectories, low contrast passages can be traversed, leading to an improved tracking performance in areas of low contrast. This work also contributes a novel ...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2009.12.003

    authors: Friman O,Hindennach M,Kühnel C,Peitgen HO

    更新日期:2010-04-01 00:00:00

  • Joint optimization of segmentation and shape prior from level-set-based statistical shape model, and its application to the automated segmentation of abdominal organs.

    abstract::The goal of this study is to provide a theoretical framework for accurately optimizing the segmentation energy considering all of the possible shapes generated from the level-set-based statistical shape model (SSM). The proposed algorithm solves the well-known open problem, in which a shape prior may not be optimal in...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2015.11.003

    authors: Saito A,Nawano S,Shimizu A

    更新日期:2016-02-01 00:00:00

  • Multiple instance learning for classification of dementia in brain MRI.

    abstract::Machine learning techniques have been widely used to detect morphological abnormalities from structural brain magnetic resonance imaging data and to support the diagnosis of neurological diseases such as dementia. In this paper, we propose to use a multiple instance learning (MIL) method in an application for the dete...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2014.04.006

    authors: Tong T,Wolz R,Gao Q,Guerrero R,Hajnal JV,Rueckert D,Alzheimer’s Disease Neuroimaging Initiative.

    更新日期:2014-07-01 00:00:00

  • Tumor sensitive matching flow: A variational method to detecting and segmenting perihepatic and perisplenic ovarian cancer metastases on contrast-enhanced abdominal CT.

    abstract::Accurate automated segmentation and detection of ovarian cancer metastases may improve the diagnosis and prognosis of women with ovarian cancer. In this paper, we focus on an important subset of ovarian cancer metastases that spread to the surface of the liver and spleen. Automated ovarian cancer metastasis detection ...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2014.04.001

    authors: Liu J,Wang S,Linguraru MG,Yao J,Summers RM

    更新日期:2014-07-01 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

  • Generalised coherent point drift for group-wise multi-dimensional analysis of diffusion brain MRI data.

    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

    authors: Ravikumar N,Gooya A,Beltrachini L,Frangi AF,Taylor ZA

    更新日期:2019-04-01 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

  • DT-MRI denoising and neuronal fiber tracking.

    abstract::Diffusion tensor imaging can provide the fundamental information required for viewing structural connectivity. However, robust and accurate acquisition and processing algorithms are needed to accurately map the nerve connectivity. In this paper, we present a novel algorithm for extracting and visualizing the fiber tra...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2003.12.001

    authors: McGraw T,Vemuri BC,Chen Y,Rao M,Mareci T

    更新日期:2004-06-01 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

  • 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

  • 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

  • Deformable organisms for automatic medical image analysis.

    abstract::We introduce a new approach to medical image analysis that combines deformable model methodologies with concepts from the field of artificial life. In particular, we propose "deformable organisms", autonomous agents whose task is the automatic segmentation, labeling, and quantitative analysis of anatomical structures ...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/s1361-8415(02)00083-x

    authors: McInerney T,Hamarneh G,Shenton M,Terzopoulos D

    更新日期:2002-09-01 00:00:00

  • Semi-supervised mp-MRI data synthesis with StitchLayer and auxiliary distance maximization.

    abstract::The availability of a large amount of annotated data is critical for many medical image analysis applications, in particular for those relying on deep learning methods which are known to be data-hungry. However, annotated medical data, especially multimodal data, is often scarce and costly to obtain. In this paper, we...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2019.101565

    authors: Wang Z,Lin Y,Cheng KT,Yang X

    更新日期:2020-01-01 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

  • Suite of meshless algorithms for accurate computation of soft tissue deformation for surgical simulation.

    abstract::The ability to predict patient-specific soft tissue deformations is key for computer-integrated surgery systems and the core enabling technology for a new era of personalized medicine. Element-Free Galerkin (EFG) methods are better suited for solving soft tissue deformation problems than the finite element method (FEM...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2019.06.004

    authors: Joldes G,Bourantas G,Zwick B,Chowdhury H,Wittek A,Agrawal S,Mountris K,Hyde D,Warfield SK,Miller K

    更新日期:2019-08-01 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