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.
authors.affiliation: Aizu Research Cluster for Medical Engineering and Informatics, Research Center for Advanced Information Science and Technology, The University of Aizu, Aizu-Wakamatsu, Fukushima 965-8580, Japan. Electronic address: tdpham@u-aizu.ac.jp.
authors.forename: Tuan D
authors.initials: TD
authors.lastname: Pham
authors.forename: Dinh T P
authors.initials: DT
authors.lastname: Le
authors.forename: Jinwei
authors.initials: J
authors.lastname: Xu
authors.forename: Duc T
authors.initials: DT
authors.lastname: Nguyen
authors.forename: Robert G
authors.initials: RG
authors.lastname: Martindale
authors.forename: Clifford W
authors.initials: CW
authors.lastname: Deveney
mesh_terms: D006555:Hernia, Ventral / Q000000981:diagnostic imaging*; D006801:Humans; D011336:Probability; D013526:Surgical Mesh; D014057:Tomography, X-Ray Computed
keywords: Abdominal wall hernia mesh; Co-occurrence matrix; Computed tomography; Geostatistical entropy; Information fusion; Pattern classification