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 classifiers which have discriminative ability from a set of selected atlases. Based on the learnt dictionaries and classifiers, probabilistic atlases are then generated to provide priors for the segmentation of unseen target images. The final segmentation is obtained by applying a post-processing step based on a graph-cuts method. In addition, this paper proposes a voxel-wise local atlas selection strategy to deal with high inter-subject variation in abdominal CT images. The segmentation performance of the proposed method with different atlas selection strategies are also compared. Our proposed method has been evaluated on a database of 150 abdominal CT images and achieves a promising segmentation performance with Dice overlap values of 94.9%, 93.6%, 71.1%, and 92.5% for liver, kidneys, pancreas, and spleen, respectively.
journal_name
Med Image Analjournal_title
Medical image analysisauthors
Tong T,Wolz R,Wang Z,Gao Q,Misawa K,Fujiwara M,Mori K,Hajnal JV,Rueckert Ddoi
10.1016/j.media.2015.04.015subject
Has Abstractpub_date
2015-07-01 00:00:00pages
92-104issue
1eissn
1361-8415issn
1361-8423pii
S1361-8415(15)00065-1journal_volume
23pub_type
杂志文章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
更新日期：2006-04-01 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：:Highly relevant for both clinical and legal medicine applications, the established radiological methods for estimating unknown age in children and adolescents are based on visual examination of bone ossification in X-ray images of the hand. Our group has initiated the development of fully automatic age estimation meth...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.101538
更新日期：2019-12-01 00:00:00
abstract：:The whole slide histopathology images (WSIs) play a critical role in gastric cancer diagnosis. However, due to the large scale of WSIs and various sizes of the abnormal area, how to select informative regions and analyze them are quite challenging during the automatic diagnosis process. The multi-instance learning bas...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.101549
更新日期：2019-12-01 00:00:00
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
更新日期：2020-10-01 00:00:00
abstract：:Cortical thickness estimation in magnetic resonance imaging (MRI) is an important technique for research on brain development and neurodegenerative diseases. This paper presents a heat kernel based cortical thickness estimation algorithm, which is driven by the graph spectrum and the heat kernel theory, to capture the...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2015.01.005
更新日期：2015-05-01 00:00:00
abstract：:Examinations of the spinal column with both, Magnetic Resonance (MR) imaging and Computed Tomography (CT), often require a precise three-dimensional positioning, angulation and labeling of the spinal disks and the vertebrae. A fully automatic and robust approach is a prerequisite for an automated scan alignment as wel...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2012.09.007
更新日期：2013-12-01 00:00:00
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
更新日期：2007-12-01 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：: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：: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：: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
更新日期：2016-01-01 00:00:00
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
更新日期：2020-08-01 00:00:00
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
更新日期：2017-10-01 00:00:00
abstract：:Accurate segmentation of the prostate and organs at risk (e.g., bladder and rectum) in CT images is a crucial step for radiation therapy in the treatment of prostate cancer. However, it is a very challenging task due to unclear boundaries, large intra- and inter-patient shape variability, and uncertain existence of bo...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.03.003
更新日期：2019-05-01 00:00:00
abstract：:It has previously been demonstrated that freehand 3D ultrasound can be acquired without a position sensor by measuring the elevational speckle decorrelation from frame to frame. However, this requires that the B-scans contain significant amounts of fully developed speckle. In this paper, we show that this condition is...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2005.08.001
更新日期：2006-04-01 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：:In this paper, we review state-of-the-art techniques to correct eye motion artifacts in Optical Coherence Tomography (OCT) imaging. The methods for eye motion artifact reduction can be categorized into two major classes: (1) hardware-based techniques and (2) software-based techniques. In the first class, additional ha...
journal_title：Medical image analysis
pub_type： 杂志文章,评审
doi：10.1016/j.media.2017.02.002
更新日期：2017-04-01 00:00:00
abstract：:This article describes a combination of interactive classification and super-sampling visualization algorithms that greatly enhances the realism of 3-D reconstructions of the Visible Human data sets. Objects are classified on the basis of ellipsoidal regions in RGB space. The ellipsoids are used for super-sampling in ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/s1361-8415(97)85001-3
更新日期：1997-09-01 00:00:00
abstract：:Statistical shape models (SSMs) have by now been firmly established as a robust tool for segmentation of medical images. While 2D models have been in use since the early 1990 s, wide-spread utilization of three-dimensional models appeared only in recent years, primarily made possible by breakthroughs in automatic dete...
journal_title：Medical image analysis
pub_type： 杂志文章,评审
doi：10.1016/j.media.2009.05.004
更新日期：2009-08-01 00:00:00
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
更新日期：2012-02-01 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：: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
更新日期：2017-01-01 00:00:00
abstract：:Synthesized medical images have several important applications. For instance, they can be used as an intermedium in cross-modality image registration or used as augmented training samples to boost the generalization capability of a classifier. In this work, we propose a generic cross-modality synthesis approach with t...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2018.12.002
更新日期：2019-02-01 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：:Deep learning-based systems can achieve a diagnostic performance comparable to physicians in a variety of medical use cases including the diagnosis of diabetic retinopathy. To be useful in clinical practice, it is necessary to have well calibrated measures of the uncertainty with which these systems report their decis...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101724
更新日期：2020-08-01 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：: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
更新日期：2003-06-01 00:00:00
abstract：:Interpretation of ultrasound videos of the fetal heart is crucial for the antenatal diagnosis of congenital heart disease (CHD). We believe that automated image analysis techniques could make an important contribution towards improving CHD detection rates. However, to our knowledge, no previous work has been done in t...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2016.11.006
更新日期：2017-02-01 00:00:00
abstract：:Over the past 20 years, the field of medical image registration has significantly advanced from multi-modal image fusion to highly non-linear, deformable image registration for a wide range of medical applications and imaging modalities, involving the compensation and analysis of physiological organ motion or of tissu...
journal_title：Medical image analysis
pub_type： 社论
doi：10.1016/j.media.2016.06.031
更新日期：2016-10-01 00:00:00
