Ovarian tissue characterization in ultrasound: a review

Acharya UR 1 , Molinari F 2 , Sree SV 3 , Swapna G 4 , Saba L 5 , Guerriero S 6 Show all authors , Suri JS 7

Affiliations 

  • 1 Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore, Singapore Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia
  • 2 Biolab, Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy filippo.molinari@polito.it
  • 3 Point-of-Care Devices Division, Global Biomedical Technologies Inc., Roseville, CA, USA
  • 4 Department of Applied Electronics and Instrumentation, Government Engineering College, Kozhikode, Kerala, India
  • 5 Department of Radiology, Azienda Ospedaliero Universitaria di Cagliari, Cagliari, Italy
  • 6 Department of Obstetrics and Gynecology, University of Cagliari, Ospedale San Giovanni di Dio, Cagliari, Italy
  • 7 Point-of-Care Devices Division, Global Biomedical Technologies Inc., Roseville, CA, USA Monitoring & Diagnostic Division, AtheroPoint LLC, Roseville, CA, USA Electrical Engineering Department, Idaho State University, (Aff.), Pocatello, ID, USA
Technol Cancer Res Treat, 2015 Jun;14(3):251-61.
PMID: 25230716 DOI: 10.1177/1533034614547445

Abstract

Ovarian cancer is the most common cause of death among gynecological malignancies. We discuss different types of clinical and nonclinical features that are used to study and analyze the differences between benign and malignant ovarian tumors. Computer-aided diagnostic (CAD) systems of high accuracy are being developed as an initial test for ovarian tumor classification instead of biopsy, which is the current gold standard diagnostic test. We also discuss different aspects of developing a reliable CAD system for the automated classification of ovarian cancer into benign and malignant types. A brief description of the commonly used classifiers in ultrasound-based CAD systems is also given.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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