A Scalable Framework For Segmenting Magnetic Resonance Images

No abstract is available for this paper.

• Publication year

  2009

• Venue

  Journal of Signal Processing Systems

• Publication date

  Unknown publication date

• Fields of study

  Medicine, Computer Science

• Identifiers
  DOI 10.1007/s11265-008-0243-1PMID 20046893PMCID PMC2771942
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Pattern Classification

  2012cited by this paper
• Autonomous Military Robotics: Risk, Ethics, and Design

  2008cited by this paper
• On evaluating brain tissue classifiers without a ground truth

  2007cited by this paper
• Creating Streaming Iterative Soft Clustering Algorithms

  2007cited by this paper
• Scalable frameworks and algorithms for cluster ensembles and clustering data streams

  2007influential reference
• A fuzzy c means variant for clustering evolving data streams

  2007cited by this paper
• Single Pass Fuzzy C Means

  2007influential reference
• A Cluster Ensemble Framework for Large Data sets

  2006cited by this paper
• Constrained Gaussian mixture model framework for automatic segmentation of MR brain images

  2006cited by this paper
• Adaptive graph cuts with tissue priors for brain MRI segmentation

  2006cited by this paper
• Fuzzy c-means clustering with spatial information for image segmentation

  2006cited by this paper
• Integrated Graph Cuts for Brain MRI Segmentation

  2006cited by this paper
• Density-Based Clustering over an Evolving Data Stream with Noise

  2006cited by this paper
• Published online in Wiley InterScience (www.interscience.wiley.com). DOI:10.1002/nbm.1025

  2006cited by this paper
• MRI brain image segmentation by adaptive spatial deterministic annealing clustering

  2006cited by this paper
• Extending fuzzy and probabilistic clustering to very large data sets

  2006cited by this paper
• Segmentation of brain MRI by adaptive mean shift

  2006cited by this paper
• MRI image segmentation using unsupervised clustering techniques

  2005cited by this paper
• Gradual model generator for single-pass clustering

  2005cited by this paper
• Summarizing complexity in high dimensions.

  2005cited by this paper
• Adaptive model initialization and deformation for automatic segmentation of T1-weighted brain MRI data

  2005cited by this paper
• Evaluation of sub-voxel registration accuracy between MRI and 3D MR spectroscopy of the brain

  2005cited by this paper
• Clustering multispectral images: a tutorial

  2005cited by this paper
• Sequence tolerant segmentation system of brain MRI

  2005cited by this paper
• Automatic segmentation of brain MRI through learning by example

  2004cited by this paper
• Proceedings of the fourth SIAM International Conference on Data Mining

  2004cited by this paper
• A Framework for Projected Clustering of High Dimensional Data Streams

  2004cited by this paper
• GenIc: A Single-Pass Generalized Incremental Algorithm for Clustering

  2004cited by this paper
• An efficient automatic framework for segmentation of MRI brain image

  2004cited by this paper
• Fast Accurate Fuzzy Clustering through Data Reduction

  2003influential reference
• A Framework for Clustering Evolving Data Streams

  2003cited by this paper
• TECNO-STREAMS: tracking evolving clusters in noisy data streams with a scalable immune system learning model

  2003cited by this paper
• Clustering Data Streams: Theory and Practice

  2003cited by this paper
• Speeding up fuzzy clustering with neural network techniques

  2003cited by this paper
• Dynamic clustering of evolving streams with a single pass

  2003cited by this paper
• Streaming-data algorithms for high-quality clustering

  2002influential reference
• Reducing the time complexity of the fuzzy c-means algorithm

  2002cited by this paper
• An accurate and efficient Bayesian method for automatic segmentation of brain MRI

  2002cited by this paper
• Complexity reduction for "large image" processing

  2002cited by this paper
• Fast robust automated brain extraction

  2002influential reference
• A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data

  2002cited by this paper
• Accelerating EM for Large Databases

  2001cited by this paper
• Automatic segmentation of non-enhancing brain tumors in magnetic resonance images

  2001cited by this paper
• Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm

  2001cited by this paper
• BOOK REVIEW: "PATTERN CLASSIFICATION", R. O. DUDA, P. E. HART and D. G. STORK, Second Edition

  2001cited by this paper
• Rapid and effective correction of RF inhomogeneity for high field magnetic resonance imaging

  2000influential reference
• IEEE International Conference on Systems, Man, and Cybernetics

  2000cited by this paper
• Scalability for clustering algorithms revisited

  2000cited by this paper
• Segmentation of 3D brain structures using level sets and dense registration

  2000cited by this paper
• Clustering very large databases using EM mixture models

  2000cited by this paper
• Current methods in medical image segmentation.

  2000cited by this paper
• Efficient fuzzy clustering of multi-spectral images

  1999cited by this paper
• Adaptive fuzzy segmentation of magnetic resonance images

  1999cited by this paper
• Automatic 3-D segmentation of internal structures of the head in MR images using a combination of similarity and free-form transformations. I. Methodology and validation on normal subjects

  1999cited by this paper
• Adaptive fuzzy c-means algorithm for image segmentation in the presence of intensity inhomogeneities

  1998cited by this paper
• Fast fuzzy clustering

  1998cited by this paper
• Scaling Clustering Algorithms to Large Databases

  1998cited by this paper
• Fully automatic segmentation of the brain in MRI

  1998cited by this paper
• Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining

  1998cited by this paper
• Automatic tumor segmentation using knowledge-based techniques

  1998cited by this paper
• MRI and PET coregistration--a cross validation of statistical parametric mapping and automated image registration.

  1997cited by this paper
• Estimating the bias field of MR images

  1997cited by this paper
• Optimization of clustering criteria by reformulation

  1995cited by this paper
• MRI segmentation using fuzzy clustering techniques

  1994cited by this paper
• Review of MR image segmentation techniques using pattern recognition.

  1993cited by this paper
• Partially supervised fuzzy c-means algorithm for segmentation of MR images

  1992cited by this paper
• Convergence theory for fuzzy c-means: Counterexamples and repairs

  1987cited by this paper
• Pattern Classification

  1973cited by this paper

• Clustering Large-scale Time Series

  2026cites this paper
• A novel fuzzy-entropy based online fuzzy C-Means clustering algorithm for massive data

  2025cites this paper
• An Approximate Maximin-Directed Random Sampling for Clustering Applications

  2023cites this paper
• C-NODDI: a constrained NODDI model for axonal density and orientation determinations in cerebral white matter

  2023cites this paper
• A Robust Learning Membership Scaling Fuzzy C-Means Algorithm Based on New Belief Peak

  2023cites this paper
• C-NODDI: a constrained NODDI model for axonal density and orientation determinations in cerebral white matter in normative aging

  2023cites this paper
• Fuzzy Clustering Algorithm Based on Improved Global Best-Guided Artificial Bee Colony with New Search Probability Model for Image Segmentation

  2022cites this paper
• Autonomous Vehicle Trajectory Combined Prediction Model Based on CC-LSTM)

  2022cites this paper
• Incremental Fuzzy Clustering Based on Feature Reduction

  2022cites this paper
• Incremental Fuzzy Clustering-Based Neural Networks Driven With the Aid of Dynamic Input Space Partition and Quasi-Fuzzy Local Models

  2022cites this paper
• A scalable eigenspace-based fuzzy c-means for topic detection

  2021cites this paper
• Personalized Preference Drift Aware Sequential Recommender System

  2021influential citation
• Hyperplane Division in Fuzzy C-Means: Clustering Big Data

  2020cites this paper
• Advance computer analysis of magnetic resonance imaging (MRI) for early brain tumor detection

  2020cites this paper
• Collaborative Framework for Fuzzy Co-clustering

  2019cites this paper
• ICFS Clustering With Multiple Representatives for Large Data

  2019cites this paper
• Ant Colony Optimization of Interval Type-2 Fuzzy C-Means with Subtractive Clustering and Multi-Round Sampling for Large Data

  2019cites this paper
• Seeding on Samples for Accelerating K-Means Clustering

  2019cites this paper
• Machine learning methods for behaviour analysis and anomaly detection in video

  2018cites this paper
• An efficient fuzzy c-means approach based on canonical polyadic decomposition for clustering big data in IoT

  2018cites this paper
• Black Hole Entropic Fuzzy Clustering

  2018cites this paper
• Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance

  2018cites this paper
• Abnormal behaviour detection at traffic junctions using Lucas Kanade and Harris Corner detector

  2018cites this paper
• Unsupervised Learning

  2018cites this paper
• Extended Fuzzy C-Means hotspot detection method for large and very large event datasets

  2018cites this paper
• A SURVEY: CHALLENGES OF IMAGE SEGMENTATION BASED FUZZY C-MEANS CLUSTERING ALGORITHM

  2018cites this paper
• Extended Gustafson–Kessel granular hotspot detection

  2018cites this paper
• Weighted Single-Pass Fuzzy c-Means Algorithm Based on Density Peaks

  2018cites this paper
• Efficient Big Data Analysis using Fuzzy Based Clustering Law with Apache Spark Proposals

  2017cites this paper
• FUZZY CLUSTERING DRIVEN FAST AND INTUITIVE CLASSIFIER LEARNING WITH MAPREDUCE FRAMEWORK

  2017cites this paper
• Detecting anomalies in crowded scenes via locality-constrained affine subspace coding

  2017cites this paper
• Deep learning and mapping based ternary change detection for information unbalanced images

  2017cites this paper
• Big Data Analysis Using Fuzzy Clustering Algorithms Implemented on Spark Framework

  2017cites this paper
• Incremental Minimax Optimization based Fuzzy Clustering for Large Multi-view Data

  2016influential citation
• Information bottleneck based incremental fuzzy clustering for large biomedical data

  2016cites this paper
• BigFCM: Fast, precise and scalable FCM on hadoop

  2016cites this paper
• A Hybrid Approach to Clustering in Big Data

  2016cites this paper
• FCM Clustering Algorithms for Segmentation of Brain MR Images

  2016cites this paper
• Fuzzy Based Clustering Algorithms to Handle Big Data with Implementation on Apache Spark

  2016cites this paper
• Fuzzy Based Scalable Clustering Algorithms for Handling Big Data Using Apache Spark

  2016cites this paper
• Big data clustering for smart city applications

  2016cites this paper
• Fuzzy -Means and Cluster Ensemble with Random Projection for Big Data Clustering

  2016cites this paper
• Incremental clustering methods and their applications on large data analysis

  2016influential citation
• MRI Brain Segmentation Using a Hybrid Artificial Bee Colony Algorithm with Fuzzy-C Mean Algorithm

  2015cites this paper
• Distributed fuzzy c-means algorithms for big sensor data based on cloud computing

  2015cites this paper
• A study of large-scale data clustering based on fuzzy clustering

  2015cites this paper
• Spatio-temporal context analysis within video volumes for anomalous-event detection and localization

  2015cites this paper
• Relational data clustering algorithms with biomedical applications

  2014cites this paper
• A HYBRID FIREFLY ALGORITHM WITH FUZZY-C MEAN ALGORITHM FOR MRI BRAIN SEGMENTATION

  2014cites this paper
• MRI brain segmentation via hybrid firefly search algorithm

  2014cites this paper
• Handling Very Large Cooccurrence Matrices in Fuzzy Co-clustering by Sampling Approaches

  2014cites this paper
• Accelerating Fuzzy-C Means Using an Estimated Subsample Size

  2014influential citation
• Multi-scale analysis of contextual information within spatio-temporal video volumes for anomaly detection

  2014influential citation
• Incremental Fuzzy Clustering With Multiple Medoids for Large Data

  2014cites this paper
• Incremental fuzzy clustering with multiple kernels

  2014cites this paper
• Incremental algorithms for fuzzy co-clustering of very large cooccurrence matrix

  2014cites this paper
• Artificial Bee Colony Based Fuzzy Clustering Algorithms For Mri Image Segmentation

  2014cites this paper
• ON FUZZY NEIGHBORHOOD BASED CLUSTERING ALGORITHM WITH LOW COMPLEXITY

  2013cites this paper
• Accelerated Fuzzy Clustering

  2013influential citation
• Dominant and Anomalous Behavior Detection in Videos

  2013influential citation
• Editor's Choice Article: Human activity recognition in videos using a single example

  2013cites this paper
• Online Dominant and Anomalous Behavior Detection in Videos

  2013influential citation
• Exploring Big Data with Scalable Soft Clustering

  2012cites this paper
• Comparison of scalable fuzzy clustering methods

  2012cites this paper
• Objective function‐based clustering

  2012cites this paper
• Fuzzy and crisp clustering methods based on the neighborhood concept: A comprehensive review

  2012cites this paper
• Fuzzy c-Means Algorithms for Very Large Data

  2012cites this paper
• Approximation of kernel k-means for streaming data

  2012cites this paper
• Convergence of the Single-Pass and Online Fuzzy C-Means Algorithms

  2011cites this paper
• Scalable fuzzy neighborhood DBSCAN

  2010cites this paper
• Incremental Kernel Fuzzy c-Means

  2010influential citation
• On convergence properties of the singlepass and online fuzzy c-means algorithm

  2010cites this paper
• A hybrid harmony search algorithm for MRI brain segmentation

  2010cites this paper
• Image segmentation using fuzzy logic, neural networks and genetic algorithms: survey and trends

  2010cites this paper
• Data clustering: 50 years beyond K-means

  2008cites this paper