Decision support system for liver cancer diagnosis using focus features in NSCT domain

Lakshmipriya Balagourouchetty, Jayanthi K. Pragatheeswaran, Biju Pottakkat, Rammkumar Govindarajalou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Diagnosis of liver cancer by medical experts using imaging modalities is found to be sub-optimal as different lesions exhibit similar visual appearance in the spatial domain. Thus computer aided diagnostic tools play a significant role in providing a decision support system for radiologists to minimize the risk of false diagnosis. This paper proposes a different feature set using focus operators for classifying different classes of liver cancer. As computation of focus measure involves the local neighborhood of pixel, focus operator is believed to indirectly measure the intricate texture details of the image. This knowledge of focus operator is exploited in NSCT domain to capture the directional components as feature variables replacing the classic texture features. The results in terms of classification accuracy and kappa coefficient proclaim that the focus operators can be employed as feature variables for classification scenario as it outperforms the state-of-the art texture features.

Original languageEnglish
Title of host publication25th National Conference on Communications, NCC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538692868
DOIs
StatePublished - Feb 2019
Externally publishedYes
Event25th National Conference on Communications, NCC 2019 - Bangalore, India
Duration: Feb 20 2019Feb 23 2019

Publication series

Name25th National Conference on Communications, NCC 2019

Conference

Conference25th National Conference on Communications, NCC 2019
Country/TerritoryIndia
CityBangalore
Period02/20/1902/23/19

Keywords

  • Classification
  • Feature extraction
  • Feature selection
  • Focus measure
  • Outliers

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