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-intensity projection and 'gallery of slices' displays, and the results suggest that the Corner Cube environment has definite advantages over both conventional display techniques. We conclude that the Corner Cube is an effective tool for summarizing the spatial characteristics of activated foci within an easily understood visual context and is especially useful for displaying the similarities and differences in functional neuroimaging datasets.
journal_name
Med Image Analjournal_title
Medical image analysisauthors
Rehm K,Lakshminaryan K,Frutiger S,Schaper KA,Sumners DW,Strother SC,Anderson JR,Rottenberg DAdoi
10.1016/s1361-8415(98)80020-0subject
Has Abstractpub_date
1998-09-01 00:00:00pages
215-26issue
3eissn
1361-8415issn
1361-8423pii
S1361-8415(98)80020-0journal_volume
2pub_type
杂志文章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：: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：: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：:Knowledge of whole heart anatomy is a prerequisite for many clinical applications. Whole heart segmentation (WHS), which delineates substructures of the heart, can be very valuable for modeling and analysis of the anatomy and functions of the heart. However, automating this segmentation can be challenging due to the l...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.101537
更新日期：2019-12-01 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：:Deep learning based methods have improved the estimation of tissue microstructure from diffusion magnetic resonance imaging (dMRI) scans acquired with a reduced number of diffusion gradients. These methods learn the mapping from diffusion signals in a voxel or patch to tissue microstructure measures. In particular, it...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101650
更新日期：2020-04-01 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：: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：: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：: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：: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...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2015.11.003
更新日期：2016-02-01 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：: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：: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：:Accurate digital representation of major white matter bundles in the brain is an important goal in neuroscience image computing since the representations can be used for surgical planning, intra-patient longitudinal analysis and inter-subject population connectivity studies. Reconstructing desired fiber bundles genera...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2018.02.008
更新日期：2018-05-01 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：:Creating a feature-preserving average of three dimensional anatomical surfaces extracted from volume image data is a complex task. Unlike individual images, averages present right-left symmetry and smooth surfaces which give insight into typical proportions. Averaging multiple biological surface images requires carefu...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/s1361-8415(00)00031-1
更新日期：2000-12-01 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：:With the development of deep learning, its application in diagnosis of benign and malignant thyroid nodules has been widely concerned. However, it is difficult to obtain medical images, resulting in insufficient number of data, which contradicts the large amount of data required for acquiring effective deep learning d...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101819
更新日期：2021-01-01 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：: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 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：: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：: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：:The distribution of cortical bone in the proximal femur is believed to be a critical component in determining fracture resistance. Current CT technology is limited in its ability to measure cortical thickness, especially in the sub-millimetre range which lies within the point spread function of today's clinical scanne...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2010.01.003
更新日期：2010-06-01 00:00:00
abstract：:A stochastic finite element framework is presented for the simultaneous estimation of the cardiac kinematic functions and material model parameters from periodic medical image sequences. While existing biomechanics studies of the myocardial material constitutive laws have assumed known tissue kinematic measurements, a...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/s1361-8415(03)00066-5
更新日期：2003-12-01 00:00:00
abstract：:We present hierarchical spherical deformation for a group-wise shape correspondence to address template selection bias and to minimize registration distortion. In this work, we aim at a continuous and smooth deformation field to guide accurate cortical surface registration. In conventional spherical registration metho...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.06.013
更新日期：2019-10-01 00:00:00
abstract：:Vascular pressure differences are established risk markers for a number of cardiovascular diseases. Relative pressures are, however, often driven by turbulence-induced flow fluctuations, where conventional non-invasive methods may yield inaccurate results. Recently, we proposed a novel method for non-turbulent flows, ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.101627
更新日期：2020-02-01 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：:Prostate brachytherapy is a treatment for prostate cancer using radioactive seeds that are permanently implanted in the prostate. The treatment success depends on adequate coverage of the target gland with a therapeutic dose, while sparing the surrounding tissue. Since seed implantation is performed under transrectal ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2012.06.001
更新日期：2012-10-01 00:00:00
