Ovarian Tissue Characterization in Ultrasound

A Review

Acharya, U. Rajendra PhD, D.Eng
Molinari, Filippo PhD
Sree, S. Vinitha
Swapna, G. ME
Saba, Luca MD
Guerriero, Stefano MD
Suri, Jasjit S. PhD, MBA

¹Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore, Singapore
²Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia
³Biolab, Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy
⁴Point-of-Care Devices Division, Global Biomedical Technologies Inc., Roseville, CA, USA
⁵Department of Applied Electronics and Instrumentation, Government Engineering College, Kozhikode, Kerala, India
⁶Department of Radiology, Azienda Ospedaliero Universitaria di Cagliari, Cagliari, Italy
⁷Department of Obstetrics and Gynecology, University of Cagliari, Ospedale San Giovanni di Dio, Cagliari, Italy
⁸Monitoring & Diagnostic Division, AtheroPoint LLC, Roseville, CA, USA
⁹Electrical Engineering Department, Idaho State University, (Aff.), Pocatello, ID, USA

Filippo Molinari, PhD, Biolab, Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy. Email: [email protected]

Received December 19, 2013

Received in revised form February 2, 2014

Accepted June 26, 2014

Technology in Cancer Research and Treatment 14(3):p 251-261, June 2015. | DOI: 10.1177/1533034614547445

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.