Cover Image
QR Code

Medical Image Retrieval Using Vector Quantization and Fuzzy S-tree.

The aim of the article is to present a novel method for fuzzy medical image retrieval (FMIR) using vector quantization (VQ) with fuzzy signatures in conjunction with fuzzy S-trees. In past times, a task of similar pictures searching was not based on searching for similar content (e.g. shapes, colour...

Full description

Published in:Journal of Medical Systems Vol. 41; no. 2; pp. 1 - 17
Main Authors: Nowaková, Jana, Prílepok, Michal, Snášel, Václav
Format: algorithm equations & formulas research tables/charts Journal Article
Published: Springer Nature Feb2017
Online Access:View this record in EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=120895338&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 120895338
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        01485598
        4N0
      jtl: Journal of Medical Systems
      issn: 01485598
      maglogo: N
    pubinfo:
      dt: Feb2017
      vid: 41
      iid: 2
      pid: 237
      pub: Springer Nature
      place: New York, New York
    artinfo:
      ui:
        120895338
        120895338
        120895338
        10.1007/s10916-016-0659-2
        120895338
      ppf: 1
      ppct: 16
      formats:
        fmt:
          @attributes:
            type: P
      tig:
        atl: Medical Image Retrieval Using Vector Quantization and Fuzzy S-tree.
      aug:
        au:
          Nowaková, Jana
          Prílepok, Michal
          Snášel, Václav
        affil: Faculty of Electrical Engineering and Computer Science, Department of Computer Science , VŠB - Technical University of Ostrava , 17. listopadu 15/2172 708 33 Ostrava - Poruba Czech Republic
      sug:
        subj:
          Image Retrieval Methods
          Image Retrieval Systems
          Mammography
          Breast Neoplasms Diagnosis
          Decision Support Systems, Clinical
          Radiographic Image Interpretation, Computer-Assisted
          Algorithms
          Magnetic Resonance Imaging
          Female
          Women's Health
          Human
          Funding Source
          Czech Republic
          Databases
          Sensitivity and Specificity
          False Positive Results
          False Negative Results
          Validity
          Descriptive Statistics
          Mammography Classification
          Female
      ab: The aim of the article is to present a novel method for fuzzy medical image retrieval (FMIR) using vector quantization (VQ) with fuzzy signatures in conjunction with fuzzy S-trees. In past times, a task of similar pictures searching was not based on searching for similar content (e.g. shapes, colour) of the pictures but on the picture name. There exist some methods for the same purpose, but there is still some space for development of more efficient methods. The proposed image retrieval system is used for finding similar images, in our case in the medical area - in mammography, in addition to the creation of the list of similar images - cases. The created list is used for assessing the nature of the finding - whether the medical finding is malignant or benign. The suggested method is compared to the method using Normalized Compression Distance (NCD) instead of fuzzy signatures and fuzzy S-tree. The method with NCD is useful for the creation of the list of similar cases for malignancy assessment, but it is not able to capture the area of interest in the image. The proposed method is going to be added to the complex decision support system to help to determine appropriate healthcare according to the experiences of similar, previous cases.
      pubtype: Academic Journal
      doctype:
        algorithm
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N