Texture recognition of medical images with the ICM method

被引:0
|
作者
Kinser, JM [1 ]
Wang, GS [1 ]
机构
[1] George Mason Univ, Inst Biosci Bioinformat & Biotech, Manassas, VA 22110 USA
关键词
textures; medical images; cortical model; pulse-image processing;
D O I
10.1016/j.nima.2004.03.101
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
The Integrated Cortical Model (ICM) is based upon several models of the mammalian visual cortex and produces pulse images over several iterations. These pulse images tend to isolate segments, edges, and textures that are inherent in the input image. To create a texture recognition engine the pulse spectrum of individual pixels are collected and used to develop a recognition library. Recognition is performed by comparing pulse spectra of unclassified regions of images with the known regions. Because signatures are smaller than images, signature-based computation is quite efficient and parasites can be recognized quickly. The precision of this method depends on the representative of signatures and classification. Our experiment results support the theoretical findings and show perspectives of practical applications of ICM-based method. The advantage of ICM method is using signatures to represent objects. ICM can extract the internal features of objects and represent them with signatures. Signature classification is critical for the precision of recognition. (C) 2004 Elsevier B.V. All rights reserved.
引用
收藏
页码:387 / 391
页数:5
相关论文
共 50 条
  • [41] SLICT: Computing Texture-Sensitive Superpixels in Medical Images
    Hou X.-D.
    Li B.-C.
    Liu H.-P.
    Du J.-Z.
    Zheng M.-J.
    Yu T.-Z.
    Zidonghua Xuebao/Acta Automatica Sinica, 2019, 45 (05): : 965 - 974
  • [42] Performance of Texture Descriptors in Classification of Medical Images with Outsiders in Database
    Avramovic, Aleksej
    Marovic, Branko
    ELEVENTH SYMPOSIUM ON NEURAL NETWORK APPLICATIONS IN ELECTRICAL ENGINEERING (NEUREL 2012), 2012,
  • [43] Analysis of texture patterns in medical images with an application to breast imaging
    Megalooikonomou, Vasileios
    Zhang, Jingjing
    Kontos, Despina
    Bakic, Predrag R.
    MEDICAL IMAGING 2007: COMPUTER-AIDED DIAGNOSIS, PTS 1 AND 2, 2007, 6514
  • [44] A statistical approach to texture description of medical images: A preliminary study
    Bevk, M
    Kononenko, I
    PROCEEDINGS OF THE 15TH IEEE SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS, 2002, : 239 - 244
  • [45] Texture Enhancement for Medical Images Based on Fractional Differential Masks
    Jalab, Hamid A.
    Ibrahim, Rabha W.
    DISCRETE DYNAMICS IN NATURE AND SOCIETY, 2013, 2013
  • [46] Query Medical Images by Cluster-Based Texture Matching
    Yang Wu
    Xu Hui
    Guo Hongxing
    Liao Mengyang(College of Electronic information
    Wuhan University Journal of Natural Sciences, 1998, (04) : 461 - 463
  • [47] Isosurface rendering of medical images improved by automatic texture mapping
    de Moraes, Thiago F.
    Amorim, Paulo H. J.
    da Silva, Jorge V. L.
    Pedrini, Helio
    COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION, 2018, 6 (04): : 379 - 385
  • [48] Retrieval by content of medical images using texture for tissue identification
    Felipe, JC
    Traina, AJM
    Traina, C
    CBMS 2003: 16TH IEEE SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS, PROCEEDINGS, 2003, : 175 - 180
  • [49] Comparison of Color, Texture and ICM Features in CBIR System
    Bhadoria, Sonali
    Madugunki, Meenakshi
    Dethe, C. G.
    Aggarwal, Preeti
    MEMS, NANO AND SMART SYSTEMS, PTS 1-6, 2012, 403-408 : 13 - +
  • [50] SELECTION OF OPTIMAL TEXTURE DESCRIPTORS FOR RETRIEVING ULTRASOUND MEDICAL IMAGES
    Sohail, Abu Sayeed Md
    Bhattacharya, Prabir
    Mudur, Sudhir P.
    Krishnamurthy, Srinivasan
    2011 8TH IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO, 2011, : 10 - 16