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 terms of an objective functional that needs to be minimized during segmentation. The algorithm allows the selection of an optimal shape prior from among all possible shapes generated from an SSM by conducting a branch-and-bound search over an eigenshape space. The proposed algorithm does not require predefined shape templates or the construction of a hierarchical clustering tree before graph-cut segmentation. It jointly optimizes an objective functional in terms of both the shape prior and segmentation labeling, and finds an optimal solution by considering all possible shapes generated from an SSM. We apply the proposed algorithm to both pancreas and spleen segmentation using multiphase computed tomography volumes, and we compare the results obtained with those produced by a conventional algorithm employing a branch-and-bound search over a search tree of predefined shapes, which were sampled discretely from an SSM. The proposed algorithm significantly improves the segmentation performance in terms of the Jaccard index and Dice similarity index. In addition, we compare the results with the state-of-the-art multiple abdominal organs segmentation algorithm, and confirmed that the performances of both algorithms are comparable to each other. We discuss the high computational efficiency of the proposed algorithm, which was determined experimentally using a normalized number of traversed nodes in a search tree, and the extensibility of the proposed algorithm to other SSMs or energy functionals.
journal_name
Med Image Analjournal_title
Medical image analysisauthors
Saito A,Nawano S,Shimizu Adoi
10.1016/j.media.2015.11.003subject
Has Abstractpub_date
2016-02-01 00:00:00pages
46-65eissn
1361-8415issn
1361-8423pii
S1361-8415(15)00180-2journal_volume
28pub_type
杂志文章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
更新日期:1998-06-01 00:00:00
abstract::The dynamics of the carotid artery wall has been recognized as a valuable indicator to evaluate the status of atherosclerotic disease in the preclinical stage. However, it is still a challenge to accurately measure this dynamics from ultrasound images. This paper aims at developing an elasticity-based state-space appr...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2017.01.004
更新日期:2017-04-01 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::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
更新日期:2003-03-01 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::Mutual information (MI) has been widely used as a similarity measure for rigid registration of multi-modal and uni-modal medical images. However, robust application of MI to deformable registration is challenging mainly because rich structural information, which are critical cues for successful deformable registration...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2013.12.003
更新日期:2014-02-01 00:00:00
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
更新日期:2013-12-01 00:00:00
abstract::In this paper, we propose a novel automated pipeline for extraction of sulcal fundi from triangulated cortical surfaces. This method consists of four consecutive steps. Firstly, we adopt a finite difference method to estimate principal curvatures, principal directions and curvature derivatives, along the principal dir...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2010.01.005
更新日期:2010-06-01 00:00:00
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
更新日期:2018-08-01 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 number of algorithms for brain segmentation in preterm born infants have been published, but a reliable comparison of their performance is lacking. The NeoBrainS12 study (http://neobrains12.isi.uu.nl), providing three different image sets of preterm born infants, was set up to provide such a comparison. These sets a...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2014.11.001
更新日期:2015-02-01 00:00:00
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
更新日期:2005-04-01 00:00:00
abstract::The spinal cord is an essential and vulnerable component of the central nervous system. Differentiating and localizing the spinal cord internal structure (i.e., gray matter vs. white matter) is critical for assessment of therapeutic impacts and determining prognosis of relevant conditions. Fortunately, new magnetic re...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2014.01.003
更新日期:2014-04-01 00:00:00
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
更新日期:2020-02-01 00:00:00
abstract::In this paper, we exploit the ability of Compressed Sensing (CS) to recover the whole 3D Diffusion MRI (dMRI) signal from a limited number of samples while efficiently recovering important diffusion features such as the Ensemble Average Propagator (EAP) and the Orientation Distribution Function (ODF). Some attempts to...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2013.02.010
更新日期:2013-07-01 00:00:00
abstract::Images of the retina acquired using optical coherence tomography (OCT) often suffer from intensity inhomogeneity problems that degrade both the quality of the images and the performance of automated algorithms utilized to measure structural changes. This intensity variation has many causes, including off-axis acquisit...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2017.09.008
更新日期:2018-01-01 00:00:00
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
更新日期:2020-12-25 00:00:00
abstract::In this work we propose a comprehensive study of Digital Stent Enhancement (DSE), from the analysis of the requirements to the validation of the proposed solution. First, we derive the stent visualization requirements in the context of the clinical application and workflow. Then, we propose a DSE algorithm combining a...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2011.03.002
更新日期:2011-08-01 00:00:00
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
更新日期:2010-04-01 00:00:00
abstract::We address the medical image analysis issue of predicting the final lesion in stroke from early perfusion magnetic resonance imaging. The classical processing approach for the dynamical perfusion images consists in a temporal deconvolution to improve the temporal signals associated with each voxel before performing pr...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2018.08.008
更新日期:2018-12-01 00:00:00
abstract::Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive impairment of memory and other cognitive functions. Currently, many multi-task learning approaches have been proposed to predict the disease progression at the early stage using longitudinal data, with each task corresponding to a pa...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2019.01.007
更新日期:2019-04-01 00:00:00
abstract::Although white matter hyperintensities evolve in the course of ageing, few solutions exist to consider the lesion segmentation problem longitudinally. Based on an existing automatic lesion segmentation algorithm, a longitudinal extension is proposed. For evaluation purposes, a longitudinal lesion simulator is created ...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2017.02.007
更新日期:2017-05-01 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::Three-dimensional (3D) freehand ultrasound uses the acquisition of non-parallel B-scans localized in 3D by a tracking system (optic, mechanical or magnetic). Using the positions of the irregularly spaced B-scans, a regular 3D lattice volume can be reconstructed, to which conventional 3D computer vision algorithms (reg...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2007.05.002
更新日期:2007-12-01 00:00:00
abstract::We propose a novel method, the adaptive local window, for improving level set segmentation technique. The window is estimated separately for each contour point, over iterations of the segmentation process, and for each individual object. Our method considers the object scale, the spatial texture, and the changes of th...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2017.01.002
更新日期:2017-04-01 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::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
更新日期:2018-01-01 00:00:00
abstract::We propose two information theoretic similarity measures that allow to incorporate tissue class information in non-rigid image registration. The first measure assumes that tissue class probabilities have been assigned to each of the images to be registered by prior segmentation of both of them. One image is then non-r...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2005.03.004
更新日期:2006-06-01 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::A new information-theoretic approach is presented for finding the registration of volumetric medical images of differing modalities. Registration is achieved by adjustment of the relative position and orientation until the mutual information between the images is maximized. In our derivation of the registration proced...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/s1361-8415(01)80004-9
更新日期:1996-03-01 00:00:00