Showing 1-25 of 423 resultsfor "Index Terms":Cortical Reconstruction
"Index Terms":Cortical Reconstruction
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A Surface-Based Approach to Quantify Local Cortical Gyrification
Marie Schaer;Meritxell Bach Cuadra;Lucas Tamarit;FranÇois Lazeyras;Stephan Eliez;Jean-Philippe Thiran
The high complexity of cortical convolutions in humans is very challenging both for engineers to measure and compare it, and for biologists and physicians to understand it. In this paper, we propose a surface-based method for the quantification of cortical gyrification. Our method uses accurate 3-D cortical reconstruction and computes local measurements of gyrification at thousands of points over ...Show More
Measuring longitudinally dynamic cortex development in infants by reconstruction of consistent cortical surfaces
Gang Li;Jingxin Nie;Li Wang;Feng Shi;John H. Gilmore;Weili Lin;Dinggang Shen
2013 IEEE 10th International Symposium on Biomedical Imaging
Year: 2013 | Conference Paper |
Cited by: Papers (1)
Quantitative measurement of dynamic cortex development during early postnatal stages is of great importance to understand early cortical structural and functional development. Conventional methods usually independently reconstruct cortical surfaces of longitudinal images from the same infant, which often generates longitudinallyinconsistent cortical surfaces and leads to inconsistence in cortex de...Show More
SurfNN: Joint Reconstruction of Multiple Cortical Surfaces from Magnetic Resonance Images
2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
To achieve fast, robust, and accurate reconstruction of the human cortical surfaces from 3D magnetic resonance images (MRIs), we develop a novel deep learning-based framework, referred to as SurfNN, to reconstruct simultaneously both inner (between white matter and gray matter) and outer (pial) surfaces from MRIs. Different from existing deep learning-based cortical surface reconstruction methods ...Show More
Cortical Bone Fracture Imaging using Velocity Model Based Multistatic Synthetic Aperture Ultrasound
Yunqing Li;Kailiang Xu;Chen Jiang;Ying Li;Chengcheng Liu;Jianqiu Zhang;Bo Hu;Dean Ta
2019 IEEE International Ultrasonics Symposium (IUS)
Year: 2019 | Conference Paper |
Cited by: Papers (1)
Compared with X-ray tomography, the use of ultrasound provides the advantages of non-ionizing radiation and low cost. However, ultrasound imaging of cortical bone fracture is still challenging due to the significant velocity changes on the interface between the cortical bone (2800-4000 m/s) and soft tissue (1400-1700 m/s). Furthermore, the low contrast-to-noise ratio (CNR) caused by artifact affec...Show More
A 3-D Ultrasound Tomography Method for Bone Morphology Evaluation
Qinzhen Shi;Tianhua Zhou;Yuan Liu;Yucheng He;Lingwei Shi;Yifang Li;Dean Ta
Accurately imaging bones using ultrasound has been a long-standing challenge, primarily due to the high attenuation, significant acoustic impedance contrast at cortical boundaries, and the unknown distribution of sound velocity. Furthermore, two-dimensional (2-D) ultrasound bone imaging has limitations in diagnosing osteoporosis from a morphological perspective, as it lacks stereoscopic spatial in...Show More
Joint analysis of cortical folding pattern, thickness and fiber density using structural and DTI data
Yixuan Yuan;Lei Guo;Gang Li;Tuo Zhang;Xintao Hu;Tianming Liu
2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro
Year: 2010 | Conference Paper |
Cortical folding is an essential geometric characteristic of the human cerebral cortex. The cortical folding pattern conveys important information about brain architecture and function. Cortical thickness is another important morphological feature that reflects the size, density, and arrangement of cells in the cortex. Meanwhile, cortical regions are connected by short-distance or long-distance wh...Show More
Detection and analysis of T2DM biomarkers from brain MR images using BrainLab
Bo Peng;Gang Li;Zhiye Chen;Bin Lv;Dinggang Shen;Lin Ma;Yakang Dai
2014 7th International Conference on Biomedical Engineering and Informatics
Year: 2014 | Conference Paper |
Cited by: Papers (1)
Detection and analysis of the brain structural abnormalities from MR images are critical for early diagnosis of type 2 diabetes mellitus (T2DM). However, to date, T2DM biomarkers from brain MR images are still not completely clear. In this study, we investigated T2DM biomarkers using BrainLab, which is our recently developed toolbox for automated analysis of brain MR images. Specifically, our subj...Show More
CortexODE: Learning Cortical Surface Reconstruction by Neural ODEs
Qiang Ma;Liu Li;Emma C. Robinson;Bernhard Kainz;Daniel Rueckert;Amir Alansary
We present CortexODE, a deep learning framework for cortical surface reconstruction. CortexODE leverages neural ordinary differential equations (ODEs) to deform an input surface into a target shape by learning a diffeomorphic flow. The trajectories of the points on the surface are modeled as ODEs, where the derivatives of their coordinates are parameterized via a learnable Lipschitz-continuous def...Show More
Residual Self-attention Based Cortical Surface Reconstruction
2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)
Year: 2022 | Conference Paper |
The accurate reconstruction of the cerebral cor-tex surface is critical for the study of neurodegenerative dis-eases. Existing voxelwise segmentation-based approaches, such as FreeSurfer and FastSurfer, are limited by the resolution of the input volume due to the partial volume effect. To address this issue, implicit surface representation based methods attempt to generate arbitrary resolution out...Show More
Cortical Surface Reconstruction via Unified Reeb Analysis of Geometric and Topological Outliers in Magnetic Resonance Images
In this paper we present a novel system for the automated reconstruction of cortical surfaces from T1-weighted magnetic resonance images. At the core of our system is a unified Reeb analysis framework for the detection and removal of geometric and topological outliers on tissue boundaries. Using intrinsic Reeb analysis, our system can pinpoint the location of spurious branches and topological outl...Show More
Index-Rotated Fast Ultrasound Imaging of Cortical Bone Based on Predicted Velocity Model
Qinzhen Shi;Yifang Li;Yuan Liu;Meilin Gu;Xiaojun Song;Chengcheng Liu;Dean Ta;Weiqi Wang
Due to the significant acoustic impedance contrast at cortical boundaries, highly inside attenuation, and the unknown sound velocity distribution, accurate ultrasound cortical bone imaging remains a challenge, especially for the traditional pulse-echo modalities using unique sound velocity. Moreover, the large amounts of data recorded by multielement probe results in a relatively time-consuming re...Show More
Automated reconstruction of the cerebral cortex in multiple sclerosis patients
2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro
Year: 2009 | Conference Paper |
Cited by: Papers (2)
Although cortical atrophy in multiple sclerosis (MS) has been reported in the literature, most cortical reconstruction techniques do not account for lesions. In this work, we propose an automated pipeline for cortical reconstruction from magnetic resonance brain images with MS lesions. The pipeline extends previously well validated methods to allow for the presence of lesions and to accommodate mu...Show More
A New Kind of Super-Resolution Reconstruction Algorithm Based on the ICM and the Bicubic Interpolation
2008 International Symposium on Intelligent Information Technology Application Workshops
Year: 2008 | Conference Paper |
Cited by: Papers (16)
Super-resolution reconstruction of image is highly dependent on the data outliers. This work addresses the super-resolution reconstruction design of the intersecting cortical model (ICM) algorithm applied to the bicubic interpolation. Based on a simplification of the pulse-coupled neural network (PCNN), we propose a design strategy to reduce the effects of outliers on the reconstructed image. Inte...Show More
A New Kind of Super-Resolution Reconstruction Algorithm Based on the ICM and the Cubic Spline Interpolation
2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop
Year: 2008 | Conference Paper |
Super-resolution reconstruction of image is highly dependent on the data outliers. This work addresses the super-resolution reconstruction design of the intersecting cortical model (ICM) algorithm applied to the cubic spline interpolation. Based on a simplification of the pulse-coupled neural network (PCNN), we propose a design strategy to reduce the effects of outliers on the reconstructed image....Show More
LOGISMOS-B: Layered Optimal Graph Image Segmentation of Multiple Objects and Surfaces for the Brain
Automated reconstruction of the cortical surface is one of the most challenging problems in the analysis of human brain magnetic resonance imaging (MRI). A desirable segmentation must be both spatially and topologically accurate, as well as robust and computationally efficient. We propose a novel algorithm, LOGISMOS-B, based on probabilistic tissue classification, generalized gradient vector flows...Show More
Ultrasound Imaging of Bone Cortex Using Block-Based Reconstruction
Yifang Li;Qinzhen Shi;Yunyun Zhang;Lexiu Xu;Wenyu Xing;Xiaojun Song;Boyi Li;Qiang Xie;Dean Ta
Without considering the significant acoustic impedance contrast between bone and soft tissue, traditional imaging methods with unique sound velocity assumption are challenging to generate accurate ultrasound image of bone cortex, such as time-domain synthetic aperture (TDSA), and phase shift migration (PSM). Furthermore, TDSA restores the image point-by-point, and PSM reconstructs the target layer...Show More
A New Kind of Super-Resolution Reconstruction Algorithm Based on the ICM and the Bilinear Interpolation
2008 International Seminar on Future BioMedical Information Engineering
Year: 2008 | Conference Paper |
Cited by: Papers (7)
Super-resolution reconstruction of image is highly dependent on the data outliers. This work addresses the super-resolution reconstruction design of the Intersecting Cortical Model (ICM) algorithm applied to the bilinear interpolation. Based on a simplification of the Pulse-Coupled Neural Network (PCNN), we propose a design strategy to reduce the effects of outliers on the reconstructed image. Int...Show More
A New Kind of Super-Resolution Reconstruction Algorithm Based on the ICM and the B-spline Interpolation
2008 International Symposium on Computer Science and Computational Technology
Year: 2008 | Conference Paper |
Super-resolution reconstruction of image is highly dependent on the data outliers. This work addresses the super-resolution reconstruction design of the intersecting cortical model (ICM) algorithm applied to the B-spline interpolation. Based on a simplification of the pulse-coupled neural network (PCNN), we propose a design strategy to reduce the effects of outliers on the reconstructed image. Int...Show More
Cortical surface reconstruction using a topology preserving geometric deformable model
Proceedings IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA 2001)
Year: 2001 | Conference Paper |
Accurate reconstruction of the cortical surface of the brain from magnetic resonance images is an important objective in biomedical image analysis. Parametric deformable surface models are usually used because they incorporate prior information, yield subvoxel accuracy, and automatically preserve topology. These algorithms are very computationally costly, however, particularly if self-intersection...Show More
Variation-based Sparse Cortical Current Density imaging in estimating cortical sources with MEG data
2010 Annual International Conference of the IEEE Engineering in Medicine and Biology
Year: 2010 | Conference Paper |
Cited by: Papers (1)
We investigated the performance of a new sparse neuroimaging method, i.e., Variation-Based Sparse Cortical Current Density (VB-SCCD) using magnetoencephalography (MEG) data to reconstruct extended cortical sources and their spatial distributions on the cortical surface. We conducted Monte Carlo simulation studies to compare the performance of the VB-SCCD method with different number of cortical so...Show More
Automatic cortical surface parcellation based on fiber density information
Degang Zhang;Lei Guo;Gang Li;Jingxin Nie;Fan Deng;Kaiming Li;Xintao Hu;Tuo Zhang;Xi Jiang;Dajiang Zhu;Qun Zhao;Tianming Liu
2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro
Year: 2010 | Conference Paper |
Cited by: Papers (11)
It is widely believed that the structural connectivity of a brain region largely determines its function. High resolution Diffusion Tensor Imaging (DTI) is now able to image the axonal fibers in vivo and the DTI tractography result provides rich connectivity information. In this paper, a novel method is proposed to employ fiber density information for automatic cortical parcellation based on the p...Show More
Cortical Volumetry Using 3D Reconstruction of Metacarpal Bone from Multi-View Images
Avinash D. Jayakar;Gautham Sambath;Anu Shaju Areeckal;S. Sumam David
2018 IEEE Recent Advances in Intelligent Computational Systems (RAICS)
Year: 2018 | Conference Paper |
Osteoporosis is a disease caused by decrease in bone density, which makes the bone more susceptible to fractures. The currently used techniques to diagnose osteoporosis such as Dual X-ray Absorptiometry (DXA) and Quantitative Computed Tomography (QCT) are expensive and not widely available. Computerized radiogrammetry is a low cost technique used for the detection of bone loss. But it gives an are...Show More
DeepCSR: A 3D Deep Learning Approach for Cortical Surface Reconstruction
Rodrigo Santa Cruz;Leo Lebrat;Pierrick Bourgeat;Clinton Fookes;Jurgen Fripp;Olivier Salvado
2021 IEEE Winter Conference on Applications of Computer Vision (WACV)
Year: 2021 | Conference Paper |
Cited by: Papers (30)
The study of neurodegenerative diseases relies on the reconstruction and analysis of the brain cortex from magnetic resonance imaging (MRI). Traditional frameworks for this task like FreeSurfer demand lengthy runtimes, while its accelerated variant FastSurfer still relies on a voxel-wise segmentation which is limited by its resolution to capture narrow continuous objects as cortical surfaces. Havi...Show More
Multiple cortical representation methods for functional localization in the human brain
2011 IEEE International Conference on Mechatronics and Automation
Year: 2011 | Conference Paper |
Using publicly available software packages (BrainVoyager, SPM, AFNI and FreeSurfer), performing multiple cortical representation methods for most of the necessary processing steps in fMRI data analyses. We will argue that specifying where in the brain activation has occurred is both conceptually and technically more difficult than has been generally assumed. In this report, we briefly presented me...Show More
Hierarchical region based ML EEG source reconstruction: A subspace projection approach
2013 21st Iranian Conference on Electrical Engineering (ICEE)
Year: 2013 | Conference Paper |
Cited by: Papers (1)
This paper presents a new method for EEG source reconstruction which is based on partitioning of cortical surface into a set of regions. The proposed method first takes advantage of subspace projection approach to determine most probable active regions in a hierarchical manner and then attempts to reach a current distribution confined to those regions. Simulation results with synthetic data show t...Show More
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