A neural network for glomerulus classification based on histological images of kidney biopsy.

Journal: BMC medical informatics and decision making
Published Date: Nov 1, 2021

Abstract

BACKGROUND: Computer-aided diagnosis (CAD) systems based on medical images could support physicians in the decision-making process. During the last decades, researchers have proposed CAD systems in several medical domains achieving promising results. CAD systems play an important role in digital pathology supporting pathologists in analyzing biopsy slides by means of standardized and objective workflows. In the proposed work, we designed and tested a novel CAD system module based on image processing techniques and machine learning, whose objective was to classify the condition affecting renal corpuscles (glomeruli) between sclerotic and non-sclerotic. Such discrimination is useful for the biopsy slides evaluation performed by pathologists.

Authors

  • Giacomo Donato Cascarano
    Department of Electrical and Information Engineering (DEI), Polytechnic University of Bari, Italy, Via Edoardo Orabona, 4, Bari, 70125, Italy.
  • Francesco Saverio Debitonto
    Department of Electrical and Information Engineering (DEI), Polytechnic University of Bari, Bary, Italy.
  • Ruggero Lemma
    Department of Electrical and Information Engineering (DEI), Polytechnic University of Bari, Bary, Italy.
  • Antonio Brunetti
    Dipartimento di Ingegneria Elettrica e dell'Informazione, Politecnico di Bari, Bari, Italy.
  • Domenico Buongiorno
    Department of Electrical and Information Engineering (DEI), Polytechnic University of Bari, Bary, Italy.
  • Irio De Feudis
    Department of Electrical and Information Engineering (DEI), Polytechnic University of Bari, Bary, Italy.
  • Andrea Guerriero
    Department of Electrical and Information Engineering (DEI), Polytechnic University of Bari, Italy, Via Edoardo Orabona, 4, Bari, 70125, Italy.
  • Umberto Venere
    Department of Emergency and Organ Transplantation, Nephrology Unit University of Bari Aldo Moro, Bari, Italy.
  • Silvia Matino
    Department of Emergency and Organ Transplantation, Nephrology Unit University of Bari Aldo Moro, Bari, Italy.
  • Maria Teresa Rocchetti
    Department of Emergency and Organ Transplantation, Nephrology Unit University of Bari Aldo Moro, Bari, Italy.
  • Michele Rossini
    Department of Emergency and Organ Transplantation, Nephrology Unit University of Bari Aldo Moro, Bari, Italy.
  • Francesco Pesce
    D.E.T.O. University of Bari Medical School, Piazza Giulio Cesare, 11, Bari, 70124, Italy.
  • Loreto Gesualdo
    Department of Diagnostic Pathology, Bioimages and Public Health, Policlinic University Hospital, Bari, Italy.
  • Vitoantonio Bevilacqua

Keywords

External Resources

Popular Topics
Recent Journals