Skip to main navigation Skip to search Skip to main content

Texture based characterization of liver tumor on computed tomography images

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Computed tomography (CT) images have been widely used for liver disease diagnosis. The CT images have been used for the analysis as these images are more clear compared to other imaging techniques. This paper focuses on developing method for classifying liver tumor from CT images using texture analysis and neural network classifier. The Co-occurrence matrices are used to extract feature like contrast, correlation, entropy, homogeneity, energy. Then the probabilistic neural network is trained to classify liver tumors as malignant and benign. The proposed system was evaluated by several liver images. It produces accuracy of 93.75%. The performance of the proposed system is also evaluated by calculating specificity, sensitivity.

Original languageEnglish
Title of host publicationInternational Conference and Workshop on Emerging Trends in Technology 2011, ICWET 2011 - Conference Proceedings
Pages141-144
Number of pages4
DOIs
Publication statusPublished - 2011
EventInternational Conference and Workshop on Emerging Trends in Technology 2011, ICWET 2011 - Mumbai, India
Duration: 25-02-201126-02-2011

Publication series

NameInternational Conference and Workshop on Emerging Trends in Technology 2011, ICWET 2011 - Conference Proceedings

Conference

ConferenceInternational Conference and Workshop on Emerging Trends in Technology 2011, ICWET 2011
Country/TerritoryIndia
CityMumbai
Period25-02-1126-02-11

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications

Fingerprint

Dive into the research topics of 'Texture based characterization of liver tumor on computed tomography images'. Together they form a unique fingerprint.

Cite this