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 computational efficiency needed for clinical applications and large database studies. In contrast, voxel-based approaches, are computationally efficient, but lack accuracy. The aim of this paper is to propose a novel voxel-based method based upon the Laplacian definition of thickness that is both accurate and computationally efficient. A framework was developed to estimate and integrate the partial volume information within the thickness estimation process. Firstly, in a Lagrangian step, the boundaries are initialized using the partial volume information. Subsequently, in an Eulerian step, a pair of partial differential equations are solved on the remaining voxels to finally compute the thickness. Using partial volume information significantly improved the accuracy of the thickness estimation on synthetic phantoms, and improved reproducibility on real data. Significant differences in the hippocampus and temporal lobe between healthy controls (NC), mild cognitive impaired (MCI) and Alzheimer's disease (AD) patients were found on clinical data from the ADNI database. We compared our method in terms of precision, computational speed and statistical power against the Eulerian approach. With a slight increase in computation time, accuracy and precision were greatly improved. Power analysis demonstrated the ability of our method to yield statistically significant results when comparing AD and NC. Overall, with our method the number of samples is reduced by 25% to find significant differences between the two groups.
journal_name
Med Image Analjournal_title
Medical image analysisauthors
Acosta O,Bourgeat P,Zuluaga MA,Fripp J,Salvado O,Ourselin S,Alzheimer's Disease Neuroimaging Initiative.doi
10.1016/j.media.2009.07.003subject
Has Abstractpub_date
2009-10-01 00:00:00pages
730-43issue
5eissn
1361-8415issn
1361-8423pii
S1361-8415(09)00049-8journal_volume
13pub_type
杂志文章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
更新日期:2010-08-01 00:00:00
abstract::Three-dimensional freehand ultrasound imaging produces a set of irregularly spaced B-scans, which are typically reconstructed on a regular grid for visualization and data analysis. Most standard reconstruction algorithms are designed to minimize computational requirements and do not exploit the underlying shape of the...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/s1361-8415(99)80028-0
更新日期:1999-12-01 00:00:00
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
更新日期:2010-08-01 00:00:00
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
更新日期:2020-01-01 00:00:00
abstract::As a common disease in the elderly, neural foramina stenosis (NFS) brings a significantly negative impact on the quality of life due to its symptoms including pain, disability, fall risk and depression. Accurate boundary delineation is essential to the clinical diagnosis and treatment of NFS. However, existing clinica...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2016.10.009
更新日期:2017-02-01 00:00:00
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
更新日期:2013-12-01 00:00:00
abstract::Alzheimers disease (AD) is a complex neurodegenerative disease. Its early diagnosis and treatment have been a major concern of researchers. Currently, the multi-modality data representation learning of this disease is gradually becoming an emerging research field, attracting widespread attention. However, in practice,...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2020.101953
更新日期:2021-01-01 00:00:00
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::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
更新日期:2021-01-01 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::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
更新日期:2018-10-01 00:00:00
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
更新日期:2005-10-01 00:00:00
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
更新日期:2002-12-01 00:00:00
abstract::Analyses of the human tongue motion as captured from 2D dynamic ultrasound data often requires segmentation of the mid-sagittal tongue contours. However, semi-automatic extraction of the tongue shape presents practical challenges. We approach this segmentation problem by proposing a novel higher-order Markov random fi...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2012.07.001
更新日期:2012-12-01 00:00:00
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
更新日期:2020-08-01 00:00:00
abstract::An automated segmentation method is presented for multi-organ segmentation in abdominal CT images. Dictionary learning and sparse coding techniques are used in the proposed method to generate target specific priors for segmentation. The method simultaneously learns dictionaries which have reconstructive power and clas...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2015.04.015
更新日期:2015-07-01 00:00:00
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
更新日期:2010-10-01 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::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::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
更新日期:2019-04-01 00:00:00
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
更新日期:2005-12-01 00:00:00
abstract::We propose HookNet, a semantic segmentation model for histopathology whole-slide images, which combines context and details via multiple branches of encoder-decoder convolutional neural networks. Concentric patches at multiple resolutions with different fields of view, feed different branches of HookNet, and intermedi...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2020.101890
更新日期:2021-02-01 00:00:00
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
更新日期:2014-07-01 00:00:00
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
更新日期:2018-05-01 00:00:00
abstract::We evaluate the accuracy of whole-body bone extraction from whole-body MR images using a number of atlas-based segmentation methods. The motivation behind this work is to find the most promising approach for the purpose of MRI-guided derivation of PET attenuation maps in whole-body PET/MRI. To this end, a variety of a...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2016.11.003
更新日期:2017-02-01 00:00:00
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
更新日期:2020-01-01 00:00:00
abstract::Many cardiac pathologies are reflected in abnormal myocardial deformation, accessible through magnetic resonance tagging (MRT). Interpretation of the MRT data is difficult, since the relation between pathology and deformation is not straightforward. Mathematical models of cardiac mechanics could be used to translate m...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2006.04.001
更新日期:2006-08-01 00:00:00
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 ...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2006.05.007
更新日期:2006-08-01 00:00:00
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
更新日期:2013-12-01 00:00:00
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
更新日期:2000-03-01 00:00:00