CNN Based Image Descriptor for Polycystic Ovarian Morphology from Transvaginal Ultrasound-Reference-Cited by-同舟云学术

CNN Based Image Descriptor for Polycystic Ovarian Morphology from Transvaginal Ultrasound

Published:2023-03-31 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Communication System, Computing and IT Applications (CSCITA)
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Author:

Panicker Pranav Hari¹,Shah Kashish²,Karamchandani Sunil³

Affiliation:

1. Indian Institute of Technology Tirupati,Dept of Electrical Engineering,Tirupati,Andhra Pradesh,India

2. University of Southern California,Viterbi School of Engineering,Los Angeles,California,USA

3. Dwarakadas J Sanghvi College of Engineering,Dept of Electronics and Telecommunication Engineering,Mumbai,Maharashtra,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10104519/10104620/10104931.pdf?arnumber=10104931

Reference9 articles.

1. Follicles Classification To Detect Polycystic Ovary Syndrome Using Glcm And Novel Hybrid Machine Learning;nilofer;Turkish Journal of Computer and Mathematics Education (TURCOMAT),2021

2. Study and detection of PCOS related diseases using CNN

3. Criteria for Polycystic Ovarian Morphology in Polycystic Ovary Syndrome as a Function of Age

4. Gabor wavelets in image processing;barina;arXiv preprint arXiv 1602 03308 (2016),0

5. Classification of polycystic ovary based on ultrasound images using competitive neural network

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3. Identification of Polycystic Ovarian Syndrome through Clinical Metrics and Ultrasonographic Imaging Analysis;2024 IEEE International Conference on Contemporary Computing and Communications (InC4);2024-03-15

4. Transfer-Based Deep Learning Technique for PCOS Detection Using Ultrasound Images;2023 International Conference on Network, Multimedia and Information Technology (NMITCON);2023-09-01