Cover Image
QR Code

Automatic Detection and Classification of Lung Nodules in CT Image Using Optimized Neuro Fuzzy Classifier with Cuckoo Search Algorithm.

The Lung nodules are very important to indicate the lung cancer, and its early detection enables timely treatment and increases the survival rate of patient. Even though lots of works are done in this area, still improvement in accuracy is required for improving the survival rate of the patient. The...

Full description

Published in:Journal of Medical Systems Vol. 43; no. 3; pp. 1 - 2
Main Authors: Manickavasagam, R., Selvan, S.
Format: diagnostic images equations & formulas tables/charts Journal Article
Published: Springer Nature Mar2019
Online Access:View this record in EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=135041244&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 135041244
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        01485598
        4N0
      jtl: Journal of Medical Systems
      issn: 01485598
      maglogo: N
    pubinfo:
      dt: Mar2019
      vid: 43
      iid: 3
      pid: 237
      pub: Springer Nature
      place: New York, New York
    artinfo:
      ui:
        135041244
        135041244
        135041244
        10.1007/s10916-019-1177-9
        135041244
      ppf: 1
      ppct: 1
      formats:
        fmt:
          – @attributes:
              type: T
          – @attributes:
              type: P
      tig:
        atl: Automatic Detection and Classification of Lung Nodules in CT Image Using Optimized Neuro Fuzzy Classifier with Cuckoo Search Algorithm.
      aug:
        au:
          Manickavasagam, R.
          Selvan, S.
        affil: HOD, Department of BME, Alpha College of Engineering, 124, Chennai, India
      sug:
        subj:
          Lung Neoplasms Diagnosis
          Early Diagnosis
          Neoplasm Staging Classification
          Tomography, X-Ray Computed
          Survival Analysis
          Algorithms
          Lung Neoplasms Radiography
          Diagnostic Imaging Evaluation
          Computer-Aided Design
          Multicenter Studies
          Image Processing, Computer Assisted
      ab: The Lung nodules are very important to indicate the lung cancer, and its early detection enables timely treatment and increases the survival rate of patient. Even though lots of works are done in this area, still improvement in accuracy is required for improving the survival rate of the patient. The proposed method can classify the stages of lung cancer in addition to the detection of lung nodules. There are two parts in the proposed method, the first part is used for classifying normal/abnormal and second part is used for classifying stages of lung cancer. Totally 10 features from the lung region segmented image are considered for detection and classification. The first part of the proposed method classifies the input images with the aid of Naive Bayes classifier as normal or abnormal. The second part of the system classifies the four stages of lung cancer using Neuro Fuzzy classifier with Cuckoo Search algorithm. The results of proposed system show that the rate of accuracy of classification is improved and the results are compared with SVM, Neural Network and Neuro Fuzzy Classifiers.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        equations & formulas
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N