Abstract：
:Sulcal pits are the points of maximal depth within the folds of the cortical surface. These shape descriptors give a unique opportunity to access to a rich, fine-scale representation of the geometry and the developmental milestones of the cortical surface. However, using sulcal pits analysis at group level requires new numerical tools to establish inter-subject correspondences. Here, we address this issue by taking advantage of the geometrical information carried by sulcal basins that are the local patches of surfaces surrounding each sulcal pit. Our framework consists in two phases. First, we present a new method to generate a population-specific atlas of this sulcal basins organi- zation as a fold-level parcellation of the cortical surface. Then, we address the labeling of individual sulcal pits and corresponding basins with respect to this atlas. To assess their validity, we applied these methodological advances on two different populations of healthy subjects. The first database of 137 adults allowed us to compare our method to the state-of-the-art and the second database of 209 children, aged between 0 and 18 years, illustrates the adaptability and relevance of our method in the context of pediatric data showing strong variations in cortical volume and folding.
journal_name
Med Image Analjournal_title
Medical image analysisauthors
Kaltenmark I,Deruelle C,Brun L,Lefèvre J,Coulon O,Auzias Gdoi
10.1016/j.media.2020.101749subject
Has Abstractpub_date
2020-12-01 00:00:00pages
101749eissn
1361-8415issn
1361-8423pii
S1361-8415(20)30113-4journal_volume
66pub_type
杂志文章abstract：:Fine-featured elastograms may provide additional information of radiological interest in the context of in vivo elastography. Here a new image processing pipeline called ESP (Elastography Software Pipeline) is developed to create Magnetic Resonance Elastography (MRE) maps of viscoelastic parameters (complex modulus ma...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2016.05.012
更新日期：2017-01-01 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：:Real-time cardiac MRI appears as a promising technique to evaluate the mechanical function of the heart. However, ultra-fast MRI acquisitions come with an important signal-to-noise ratio (SNR) penalty, which drastically reduces the image quality. Hence, a real-time denoising approach would be desirable for SNR amelior...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2009.05.006
更新日期：2009-08-01 00:00:00
abstract：:Biophysical models of the atrium provide a physically constrained framework for describing the current state of an atrium and allow predictions of how that atrium will respond to therapy. We propose a work flow to simulate patient specific electrophysiological heterogeneity from clinical data and validate the resultin...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2018.04.005
更新日期：2018-07-01 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：: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 have developed a new technique for extracting histological parameters from multi-spectral images of the ocular fundus. The new method uses a Monte Carlo simulation of the reflectance of the fundus to model how the spectral reflectance of the tissue varies with differing tissue histology. The model is parameterised ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2006.05.007
更新日期：2006-08-01 00:00:00
abstract：:This paper presents a new hybrid camera motion tracking method for bronchoscopic navigation combining SIFT, epipolar geometry analysis, Kalman filtering, and image registration. In a thorough evaluation, we compare it to state-of-the-art tracking methods. Our hybrid algorithm for predicting bronchoscope motion uses SI...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2010.11.001
更新日期：2012-04-01 00:00:00
abstract：:Accurate ventricular volume measurements are the primary indicators of normal/abnor- mal cardiac function and are dependent on the Cardiac Magnetic Resonance (CMR) volumes being complete. However, missing or unusable slices owing to the presence of image artefacts such as respiratory or motion ghosting, aliasing, ring...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101812
更新日期：2021-01-01 00:00:00
abstract：:In minimally invasive surgery, deployment of motion compensation, dynamic active constraints and adaptive intra-operative guidance require accurate estimation of deforming tissue in 3D. To this end, the use of vision-based techniques is advantageous in that it does not require the integration of additional hardware to...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2011.02.010
更新日期：2012-04-01 00:00:00
abstract：:After two decades of increasing interest and research activity, computer-assisted diagnostic approaches are reaching the stage where more routine deployment in clinical practice is becoming a possibility [Kruppinski, E.A., 2004. Computer-aided detection in clinical environment: Benefits and challenges for radiologists...
journal_title：Medical image analysis
pub_type： 杂志文章,评审
doi：10.1016/j.media.2005.06.003
更新日期：2006-04-01 00:00:00
abstract：:An automatic detection method for 197 anatomically defined landmarks in computed tomography (CT) volumes is presented. The proposed method can handle missed landmarks caused by detection failure, a limited imaging range and other problems using a novel combinatorial optimization framework with a two-stage sampling alg...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2016.04.001
更新日期：2017-01-01 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：:Diffusion weighted imaging (DWI) is sensitive to alterations in the diffusion of water molecules caused by microstructural barriers. Different microstructural compartments are characterized by differences in DWI signal. Diffusion tensor imaging conflates the signal from these compartments into a single tensor, which p...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2015.10.004
更新日期：2015-12-01 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：:The eye affords a unique opportunity to inspect a rich part of the human microvasculature non-invasively via retinal imaging. Retinal blood vessel segmentation and classification are prime steps for the diagnosis and risk assessment of microvascular and systemic diseases. A high volume of techniques based on deep lear...
journal_title：Medical image analysis
pub_type： 杂志文章,评审
doi：10.1016/j.media.2020.101905
更新日期：2021-02-01 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：: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：:The ability to predict patient-specific soft tissue deformations is key for computer-integrated surgery systems and the core enabling technology for a new era of personalized medicine. Element-Free Galerkin (EFG) methods are better suited for solving soft tissue deformation problems than the finite element method (FEM...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.06.004
更新日期：2019-08-01 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：: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：: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：: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：: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：:An automated vendor-independent system for dose monitoring in computed tomography (CT) medical examinations involving ionizing radiation is presented in this paper. The system provides precise size-specific dose estimates (SSDE) following the American Association of Physicists in Medicine regulations. Our dose managem...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101898
更新日期：2021-02-01 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：: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：: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：:With the advent of large-scale imaging studies and big health data, and the corresponding growth in analytics, machine learning and computational image analysis methods, there are now exciting opportunities for deepening our understanding of the mechanisms and characteristics of heart disease. Two emerging fields are ...
journal_title：Medical image analysis
pub_type： 社论,评审
doi：10.1016/j.media.2016.06.027
更新日期：2016-10-01 00:00:00
abstract：:Fast and accurate 2D/3D registration plays an important role in many applications, ranging from scientific and engineering domains all the way to medical care. Today's predominant methods are based on computationally expensive approaches, such as virtual forward or back projections, that limit the real-time applicabil...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101815
更新日期：2021-01-01 00:00:00
