Journal article Open Access

Automatic Liver Cancer Detection using Sobel Edge Detection & Morphological Dilation in Digital Image Processing

Vijay Laxmi Yadav; Anubhuti Khare


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  <identifier identifierType="URL">https://zenodo.org/record/5848193</identifier>
  <creators>
    <creator>
      <creatorName>Vijay Laxmi Yadav</creatorName>
      <affiliation>Dept. of Electronics and Communication, University Institute of Technology, Rajiv Gandhi Proudyogiki  Vishwavidyalaya, Bhopal, Madhya Pradesh, India.</affiliation>
    </creator>
    <creator>
      <creatorName>Anubhuti Khare</creatorName>
      <affiliation>Dept. of Electronics and Communication, University Institute of Technology, Rajiv Gandhi Proudyogiki  Vishwavidyalaya, Bhopal, Madhya Pradesh, India.</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Automatic Liver Cancer Detection using Sobel  Edge Detection &amp; Morphological Dilation in  Digital Image Processing</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <subjects>
    <subject>Liver Cancer Detection, Sobel Edge Detection, Morphological Dilation, CT Scans, Segmentation.</subject>
    <subject subjectScheme="issn">2278-3075</subject>
    <subject subjectScheme="handle">100.1/ijitee.L80111091220</subject>
  </subjects>
  <contributors>
    <contributor contributorType="Sponsor">
      <contributorName>Blue Eyes Intelligence Engineering  and Sciences Publication(BEIESP)</contributorName>
      <affiliation>Publisher</affiliation>
    </contributor>
  </contributors>
  <dates>
    <date dateType="Issued">2020-10-30</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="JournalArticle"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/5848193</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="ISSN" relationType="IsCitedBy" resourceTypeGeneral="JournalArticle">2278-3075</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.35940/ijitee.L8011.1091220</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Image processing is a field that is widely used in medical science to identify various cancers or tumors. Diagnosing liver cancer is not an easy task and is usually performed by doctors and diagnosed manually. Filtering technique should be used precisely by not compromising the sensitive information. Most of the technique may distort the actual information that causes false alarm rate. A liver is an uneven or bit complex in structure where there are various spots may be considered as tumor that provokes the system towards invalid turing test. This paper proposes a system that would be able to recognize cancer automatically from a tomographical image along with high precision that stabilize the system with less processing time. Here the objective of the system is to obtain the result using Sobel operator that retains edges and eroding the unwanted areas and preceding high accuracy with less error rate. System also intended to extract the impaired area that has been affected by liver cancer. System acquired the better precision rate as compare to the previously implemented systems with minimal error rate.&lt;/p&gt;</description>
  </descriptions>
</resource>
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