Abstract：
:In this note we summarize the history of computer aided surgery in orthopaedics and traumatology from the end of the nineteenth century to currently observable future trends. We concentrate on the two major components of such systems, pre-operative planning and intra-operative execution. The evolution of the necessary technological components, the numerous platforms and components offered commercially as well as their clinical use are surveyed.
journal_name
Med Image Analjournal_title
Medical image analysisauthors
Székely G,Nolte LPdoi
10.1016/j.media.2016.06.033subject
Has Abstractpub_date
2016-10-01 00:00:00pages
79-83eissn
1361-8415issn
1361-8423pii
S1361-8415(16)30110-4journal_volume
33pub_type
社论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 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
更新日期：2002-09-01 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：: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：:Diffusion MRI magnitude data, typically Rician or noncentral χ distributed, is affected by the noise floor, which falsely elevates signal, reduces image contrast, and biases estimation of diffusion parameters. Noise floor can be avoided by extracting real-valued Gaussian-distributed data from complex diffusion-weighte...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101828
更新日期：2021-02-01 00:00:00
abstract：:In this paper, we present a generative Bayesian approach for estimating the low-dimensional latent space of diffeomorphic shape variability in a population of images. We develop a latent variable model for principal geodesic analysis (PGA) that provides a probabilistic framework for factor analysis in the space of dif...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2015.04.009
更新日期：2015-10-01 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：:Automated ventricle volume estimation (AVVE) on cardiac magnetic resonance (CMR) images is very important for clinical cardiac disease diagnosis. However, current AVVE methods ignore the error correction for the estimated volume. This results in clinically intolerable ventricle volume estimation error and further lead...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101723
更新日期：2020-08-01 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：:A new method is proposed to quantify the myocardial motion from both 2D C(ine)-MRI and T(agged)-MRI sequences. The tag pattern offers natural landmarks within the image that makes it possible to accurately quantify the motion within the myocardial wall. Therefore, several methods have been proposed for T-MRI. However,...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.06.016
更新日期：2019-10-01 00:00:00
abstract：:The Insight Toolkit (ITK) initiative from the National Library of Medicine has provided a suite of state-of-the-art segmentation and registration algorithms ideally suited to volume visualization and analysis. A volume visualization application that effectively utilizes these algorithms provides many benefits: it allo...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2005.04.009
更新日期：2005-12-01 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：:In this work, various wavelet based methods like the discrete wavelet transform, the dual-tree complex wavelet transform, the Gabor wavelet transform, curvelets, contourlets and shearlets are applied for the automated classification of colonic polyps. The methods are tested on 8 HD-endoscopic image databases, where ea...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2016.02.001
更新日期：2016-07-01 00:00:00
abstract：:Classification of digital pathology images is imperative in cancer diagnosis and prognosis. Recent advancements in deep learning and computer vision have greatly benefited the pathology workflow by developing automated solutions for classification tasks. However, the cost and time for acquiring high quality task-speci...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101859
更新日期：2021-01-01 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：: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：: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：:Robust and fast detection of anatomical structures represents an important component of medical image analysis technologies. Current solutions for anatomy detection are based on machine learning, and are generally driven by suboptimal and exhaustive search strategies. In particular, these techniques do not effectively...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2018.06.007
更新日期：2018-08-01 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：:In this paper, we propose a new strategy for modelling sliding conditions when registering 3D images in a piecewise-diffeomorphic framework. More specifically, our main contribution is the development of a mathematical formalism to perform Large Deformation Diffeomorphic Metric Mapping registration with sliding condit...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2012.10.001
更新日期：2013-02-01 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：:Independent component analysis (ICA) is a statistical technique that estimates a set of sources mixed by an unknown mixing matrix using only a set of observations. For this purpose, the only assumption is that the sources are statistically independent. In many applications, some information about the nature of the unk...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2010.06.009
更新日期：2011-02-01 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：:This paper presents a symbolic visualization environment known as the Corner Cube environment, which was developed to facilitate rapid examination and comparison of activated foci defined by analyses of functional neuroimaging datasets. We have performed a comparative evaluation of this environment against maximum-int...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/s1361-8415(98)80020-0
更新日期：1998-09-01 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：:Lung CAD systems require the ability to classify a variety of pulmonary structures as part of the diagnostic process. The purpose of this work was to develop a methodology for fully automated voxel-by-voxel classification of airways, fissures, nodules, and vessels from chest CT images using a single feature set and cl...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2007.03.004
更新日期：2007-06-01 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 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：: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 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
