Image processing methods for the structural detection and gradation of placental villi.

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  • Additional Information
    • Source:
      Publisher: Elsevier Country of Publication: United States NLM ID: 1250250 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-0534 (Electronic) Linking ISSN: 00104825 NLM ISO Abbreviation: Comput Biol Med
    • Publication Information:
      Publication: New York : Elsevier
      Original Publication: New York, Pergamon Press.
    • Subject Terms:
      Abortion, Spontaneous*/metabolism ; Abortion, Spontaneous*/pathology ; Chorionic Villi*/metabolism ; Chorionic Villi*/pathology; Image Processing, Computer-Assisted/*methods; Adult ; Female ; Humans ; Pregnancy
    • Abstract:
      The context-based examination of stained tissue specimens is one of the most important procedures in histopathological practice. The development of image processing methods allows for the automation of this process. We propose a method of automatic segmentation of placental structures and assessment of edema present in placental structures from a spontaneous miscarriage. The presented method is based on texture analysis, mathematical morphology, and region growing operations that are applicable to the heterogeneous microscopic images representing histological slides of the placenta. The results presented in this study were obtained using a set of 50 images of single villi originating from 13 histological slides and was compared with the manual evaluation of the pathologist. In the presented experiments, various structures, such as villi, villous mesenchyme, trophoblast, collagen, and vessels have been recognized. Moreover, the gradation of villous edema for three classes (no villous edema, moderate villous edema, and massive villous edema) has been conducted. Villi images were correctly identified in 98.21%, villous mesenchyme was correctly identified in 83.95%, and the villi evaluation was correct in 74% for the edema degree and 86% for the number of vessels. The presented segmentation method may serve as a support for current manual diagnosis methods and reduce the bias related to individual, subjective assessment of experts.
      (Copyright © 2017 Elsevier Ltd. All rights reserved.)
    • Contributed Indexing:
      Keywords: Histopathology; Image analysis; Image segmentation; Mathematical morphology; Placenta; Texture
    • Publication Date:
      Date Created: 20170812 Date Completed: 20190806 Latest Revision: 20190806
    • Publication Date:
      20221213
    • Accession Number:
      10.1016/j.compbiomed.2017.08.004
    • Accession Number:
      28797713