Detection of Ovarian Cyst in Ultrasound Images using Super pixel segmentation method

Christy Esther S , Mohanasundaram K , Joanna Blessy

Cyst detection, Ovarian cyst, Polycystic ovarian syndrome, super pixel algorithm.

Detection of cyst in the ovary is as essential as to treat the patient with Polycystic Ovarian Syndrome (PCOS). Manual methods to diagonise an ovarian cyst in ultrasound image have always produced results with some error. Many automated algorithms have been used for ovarian cyst detection in ultrasound images. This paper discusses the detection of cyst in ovarian ultrasound image with an accuracy reaching 90%, using the super pixel Algorithm.

Published Paper   E-Certificate

"Detection of Ovarian Cyst in Ultrasound Images using Super pixel segmentation method ", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.5, Issue 4, page no.213 - 215, April-2020, Available :https://ijsdr.org/papers/IJSDR2004036.pdf

Volume 5 Issue 4, April-2020

Pages : 213 - 215

Paper Reg. ID: IJSDR_191606

Published Paper Id: IJSDR2004036

Downloads: 000347362

Research Area: Engineering

Country: Coimbatore, Tamilnadu, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2004036

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2004036

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition