Personalized identification of abdominal wall hernia meshes on computed tomography

Tuan D. Pham, Dinh T.P. Le, Jinwei Xu, Duc T. Nguyen, Robert G. Martindale, Clifford W. Deveney

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

An abdominal wall hernia is a protrusion of the intestine through an opening or area of weakness in the abdominal wall. Correct pre-operative identification of abdominal wall hernia meshes could help surgeons adjust the surgical plan to meet the expected difficulty and morbidity of operating through or removing the previous mesh. First, we present herein for the first time the application of image analysis for automated identification of hernia meshes. Second, we discuss the novel development of a new entropy-based image texture feature using geostatistics and indicator kriging. Third, we seek to enhance the hernia mesh identification by combining the new texture feature with the gray-level co-occurrence matrix feature of the image. The two features can characterize complementary information of anatomic details of the abdominal hernia wall and its mesh on computed tomography. Experimental results have demonstrated the effectiveness of the proposed study. The new computational tool has potential for personalized mesh identification which can assist surgeons in the diagnosis and repair of complex abdominal wall hernias.

Original languageEnglish (US)
Pages (from-to)153-161
Number of pages9
JournalComputer Methods and Programs in Biomedicine
Volume113
Issue number1
DOIs
StatePublished - Jan 1 2014

Keywords

  • Abdominal wall hernia mesh
  • Co-occurrence matrix
  • Computed tomography
  • Geostatistical entropy
  • Information fusion
  • Pattern classification

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Health Informatics

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