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Image Segmentation for detecting Polycystic Ovarian Disease using Deep Neural Networks

Palvi Soni1 , Sheveta Vashisht2

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-3 , Page no. 534-537, Mar-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i3.534537

Online published on Mar 31, 2019

Copyright © Palvi Soni, Sheveta Vashisht . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Palvi Soni, Sheveta Vashisht, “Image Segmentation for detecting Polycystic Ovarian Disease using Deep Neural Networks,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.534-537, 2019.

MLA Style Citation: Palvi Soni, Sheveta Vashisht "Image Segmentation for detecting Polycystic Ovarian Disease using Deep Neural Networks." International Journal of Computer Sciences and Engineering 7.3 (2019): 534-537.

APA Style Citation: Palvi Soni, Sheveta Vashisht, (2019). Image Segmentation for detecting Polycystic Ovarian Disease using Deep Neural Networks. International Journal of Computer Sciences and Engineering, 7(3), 534-537.

BibTex Style Citation:
@article{Soni_2019,
author = {Palvi Soni, Sheveta Vashisht},
title = {Image Segmentation for detecting Polycystic Ovarian Disease using Deep Neural Networks},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2019},
volume = {7},
Issue = {3},
month = {3},
year = {2019},
issn = {2347-2693},
pages = {534-537},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3875},
doi = {https://doi.org/10.26438/ijcse/v7i3.534537}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i3.534537}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3875
TI - Image Segmentation for detecting Polycystic Ovarian Disease using Deep Neural Networks
T2 - International Journal of Computer Sciences and Engineering
AU - Palvi Soni, Sheveta Vashisht
PY - 2019
DA - 2019/03/31
PB - IJCSE, Indore, INDIA
SP - 534-537
IS - 3
VL - 7
SN - 2347-2693
ER -

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Abstract

Polycystic Ovaries in females in today’s age is a matter of concern.It can hinder the fertile nature of female and cause many more issues.Polycystic Ovaries can be detected by ultrasound.It can create a lot of problems if not taken seriously.For leading a good life females should be aware of this disease also.In approximate 70 per cent of this kind of cases remain undiagnosed. In past studies feature extraction using Convolutional Neural Network has proposed manually,here we try to propose a methodology in which we will add segmentation prior CNN so as to delete or eliminate redundant data and to achieve better accuarcy .Segmentation allows to divide the data or images so as deeply extract the exact information what is needed.

Key-Words / Index Term

Deep neural network,region growing,CNN

References

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