Abstract：
:We describe a new 3-D statistical shape model of the heart consisting of atria, ventricles and epicardium. The model was constructed by combining information on standard short- and long-axis cardiac MR images. In the model, the variability of the shape was modeled with PCA- and ICA-based shape models as well as with non-parametric landmark probability distributions and a probabilistic atlas. The statistical atlas was built from 25 healthy subjects. The shape model was evaluated by applying it to image segmentation. The probabilistic atlas was found to be superior to the other shape models (P < 0.001) in this study.
journal_name
Med Image Analjournal_title
Medical image analysisauthors
Lötjönen J,Kivistö S,Koikkalainen J,Smutek D,Lauerma Kdoi
10.1016/j.media.2004.06.013subject
Has Abstractpub_date
2004-09-01 00:00:00pages
371-86issue
3eissn
1361-8415issn
1361-8423pii
S1361841504000374journal_volume
8pub_type
杂志文章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：:Retinal images are routinely acquired and assessed to provide diagnostic evidence for many important diseases, e.g. diabetes or hypertension. Because of the acquisition process, very often these images are non-uniformly illuminated and exhibit local luminosity and contrast variability. This problem may seriously affec...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2004.07.001
更新日期：2005-06-01 00:00:00
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
更新日期：1998-12-01 00:00:00
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
更新日期：2020-05-01 00:00:00
abstract：:The problem of respiratory motion has proved a serious obstacle in developing techniques to acquire images or guide interventions in abdominal and thoracic organs. Motion models offer a possible solution to these problems, and as a result the field of respiratory motion modelling has become an active one over the past...
journal_title：Medical image analysis
pub_type： 杂志文章,评审
doi：10.1016/j.media.2012.09.005
更新日期：2013-01-01 00:00:00
abstract：:Numerous algorithms are available for segmenting medical images. Empirical discrepancy metrics are commonly used in measuring the similarity or difference between segmentations by algorithms and "true" segmentations. However, one issue with the commonly used metrics is that the same metric value often represents diffe...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.101601
更新日期：2020-02-01 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：:Diffusion magnetic resonance imaging (dMRI) provides a noninvasive method for measuring brain tissue microstructure. q-Space deep learning(q-DL) methods have been developed to accurately estimate tissue microstructure from dMRI scans acquired with a reduced number of diffusion gradients. In these methods, deep network...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101885
更新日期：2021-01-01 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：: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
更新日期：2019-07-01 00:00:00
abstract：:This paper introduces a model-based approach for a fully automatic delineation of kidney and cortex tissue from contrast-enhanced abdominal CT scans. The proposed framework, named CorteXpert, consists of two new strategies for kidney tissue delineation: cortex model adaptation and non-uniform graph search. CorteXpert ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2017.06.010
更新日期：2017-12-01 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：: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
更新日期：2014-10-01 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
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：:Segmentation of the geometric morphology of abdominal aortic aneurysm is important for interventional planning. However, the segmentation of both the lumen and the outer wall of aneurysm in magnetic resonance (MR) image remains challenging. This study proposes a registration based segmentation methodology for efficien...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2017.05.005
更新日期：2017-08-01 00:00:00
abstract：:Registration of three-dimensional ultrasound (3DUS) volumes is necessary in several applications, such as when stitching volumes to expand the field of view or when stabilizing a temporal sequence of volumes to cancel out motion of the probe or anatomy. Current systems that register 3DUS volumes either use external tr...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2011.10.004
更新日期：2012-02-01 00:00:00
abstract：:In this paper, we present a new method for the automatic comparison of myocardial motion patterns and the characterization of their degree of abnormality, based on a statistical atlas of motion built from a reference healthy population. Our main contribution is the computation of atlas-based indexes that quantify the ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2010.12.006
更新日期：2011-06-01 00:00:00
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
更新日期：2019-04-01 00:00:00
abstract：:Accurate vertebral body (VB) detection and segmentation are critical for spine disease identification and diagnosis. Existing automatic VB detection and segmentation methods may cause false-positive results to the background tissue or inaccurate results to the desirable VB. Because they usually cannot take both the gl...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101861
更新日期：2021-01-01 00:00:00
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
更新日期：2012-07-01 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：:Clinical acceptance of 3-D OCT retinal imaging brought rapid development of quantitative 3-D analysis of retinal layers, vasculature, retinal lesions as well as facilitated new research in retinal diseases. One of the cornerstones of many such analyses is segmentation and thickness quantification of retinal layers and...
journal_title：Medical image analysis
pub_type： 社论
doi：10.1016/j.media.2016.06.001
更新日期：2016-10-01 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：: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：: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
更新日期：2020-02-01 00:00:00
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
更新日期：2017-01-01 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 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：: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
