Segmentation and clustering in brain MRI imaging

被引：51
|
作者：
Mirzaei, Golrokh [4 ]
Adeli, Hojjat [1 ,2 ,3 ]
机构：
[1] Ohio State Univ, Dept Biomed Informat, Columbus, OH 43210 USA
[2] Ohio State Univ, Dept Neurol, Columbus, OH 43210 USA
[3] Ohio State Univ, Dept Neurosci, Columbus, OH 43210 USA
[4] Ohio State Univ, Dept Comp Sci & Engn, Marion, OH 43302 USA
来源：
REVIEWS IN THE NEUROSCIENCES | 2019年 / 30卷 / 01期
关键词：
clustering; convolutional neural network; FCM; K-means; segmentation; CONVOLUTIONAL NEURAL-NETWORKS; ANT COLONY OPTIMIZATION; DEEP LEARNING-MODEL; C-MEANS ALGORITHM; TUMOR SEGMENTATION; FEATURE-EXTRACTION; DAMAGE DETECTION; SWARM; CNN; DESIGN;
D O I：
10.1515/revneuro-2018-0050
中图分类号：
Q189 [神经科学];
学科分类号：
071006 ;
摘要：
Clustering is a vital task in magnetic resonance imaging (MRI) brain imaging and plays an important role in the reliability of brain disease detection, diagnosis, and effectiveness of the treatment. Clustering is used in processing and analysis of brain images for different tasks, including segmentation of brain regions and tissues (grey matter, white matter, and cerebrospinal fluid) and clustering of the atrophy in different parts of the brain. This paper presents a state-of-the-art review of brain MRI studies that use clustering techniques for different tasks.
引用
收藏
页码：31 / 44
页数：14
相关论文
共 50 条
  • [41] Brain MRI Segmentation for Tumor Detection using Grammatical Swarm Based Clustering Algorithm
    Si, Tapas
    De, Arunava
    Bhattacharjee, Anup Kumar
    2014 IEEE INTERNATIONAL CONFERENCE ON CIRCUIT, POWER AND COMPUTING TECHNOLOGIES (ICCPCT-2014), 2014, : 1196 - 1201
  • [42] Performance analysis of unsupervised optimal fuzzy clustering algorithm for MRI brain tumor segmentation
    Blessya, S. A. Praylin Selva
    Sulochana, C. Helen
    TECHNOLOGY AND HEALTH CARE, 2015, 23 (01) : 23 - 35
  • [43] Segmentation of Brain MRI Images By Using Type-II Fuzzy Clustering Algorithm
    Toker, Ipek
    Dogan, Berat
    Pinar, Sedef Kent
    2015 23RD SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2015, : 1909 - 1912
  • [44] Brain MRI Segmentation for Lesion Detection Using Clustering with Fire-Fly Algorithm
    Manna, Pramita
    Si, Tapas
    ARTIFICIAL INTELLIGENCE AND EVOLUTIONARY COMPUTATIONS IN ENGINEERING SYSTEMS, ICAIECES 2015, 2016, 394 : 1347 - 1355
  • [45] Segmentation for brain MRI image based on the fuzzy c-means clustering algorithm
    Yin, Xi
    Li, Yimin
    Li, Feng
    INFORMATION SCIENCE AND MANAGEMENT ENGINEERING, VOLS 1-3, 2014, 46 : 1177 - 1182
  • [46] Fuzzy Clustering and Deformable Model for Tumor Segmentation on MRI Brain Image: A Combined Approach
    Rajendran, A.
    Dhanasekaran, R.
    INTERNATIONAL CONFERENCE ON COMMUNICATION TECHNOLOGY AND SYSTEM DESIGN 2011, 2012, 30 : 327 - 333
  • [47] Bayesian Markov model for cooperative clustering: application to robust MRI brain scan segmentation
    Forbes, Florence
    Scherrer, Benoit
    Dojat, Michel
    JOURNAL OF THE SFDS, 2011, 152 (03): : 116 - 141
  • [48] Automatic segmentation of the brain in MRI
    Atkins, M.S.
    Mackiewich, B.T.
    Lecture Notes in Computer Science, 1131
  • [49] MRI brain images segmentation
    He, SJ
    Wang, X
    Yang, YM
    Yan, WL
    2000 IEEE ASIA-PACIFIC CONFERENCE ON CIRCUITS AND SYSTEMS: ELECTRONIC COMMUNICATION SYSTEMS, 2000, : 113 - 116
  • [50] Tissue Segmentation of Brain MRI
    Dvorak, Pavel
    Bartusek, Karel
    Mikulka, Jan
    2015 38TH INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS AND SIGNAL PROCESSING (TSP), 2015, : 735 - 738
12345