Personalized identification of abdominal wall hernia meshes on computed tomography

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

Research output: Contribution to journalArticle

10 Citations (Scopus)

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 2014

Fingerprint

Abdominal Hernia
Image texture
Abdominal Wall
Image analysis
Tomography
Repair
Entropy
Textures
Hernia
Spatial Analysis
Intestines
Morbidity

Keywords

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

ASJC Scopus subject areas

  • Computer Science Applications
  • Software
  • Health Informatics

Cite this

Personalized identification of abdominal wall hernia meshes on computed tomography. / Pham, Tuan D.; Le, Dinh T P; Xu, Jinwei; Nguyen, Duc T.; Martindale, Robert; Deveney, Clifford.

In: Computer Methods and Programs in Biomedicine, Vol. 113, No. 1, 01.2014, p. 153-161.

Research output: Contribution to journalArticle

@article{e4a6aa0830c44d78918f666d47c89567,
title = "Personalized identification of abdominal wall hernia meshes on computed tomography",
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.",
keywords = "Abdominal wall hernia mesh, Co-occurrence matrix, Computed tomography, Geostatistical entropy, Information fusion, Pattern classification",
author = "Pham, {Tuan D.} and Le, {Dinh T P} and Jinwei Xu and Nguyen, {Duc T.} and Robert Martindale and Clifford Deveney",
year = "2014",
month = "1",
doi = "10.1016/j.cmpb.2013.09.019",
language = "English (US)",
volume = "113",
pages = "153--161",
journal = "Computer Methods and Programs in Biomedicine",
issn = "0169-2607",
publisher = "Elsevier Ireland Ltd",
number = "1",

}

TY - JOUR

T1 - Personalized identification of abdominal wall hernia meshes on computed tomography

AU - Pham, Tuan D.

AU - Le, Dinh T P

AU - Xu, Jinwei

AU - Nguyen, Duc T.

AU - Martindale, Robert

AU - Deveney, Clifford

PY - 2014/1

Y1 - 2014/1

N2 - 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.

AB - 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.

KW - Abdominal wall hernia mesh

KW - Co-occurrence matrix

KW - Computed tomography

KW - Geostatistical entropy

KW - Information fusion

KW - Pattern classification

UR - http://www.scopus.com/inward/record.url?scp=84887828146&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84887828146&partnerID=8YFLogxK

U2 - 10.1016/j.cmpb.2013.09.019

DO - 10.1016/j.cmpb.2013.09.019

M3 - Article

VL - 113

SP - 153

EP - 161

JO - Computer Methods and Programs in Biomedicine

JF - Computer Methods and Programs in Biomedicine

SN - 0169-2607

IS - 1

ER -