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Automated Cancer Diagnosis Identification System using Image Segmentation and Threshold Filter

Rukmani Kushwaha1 , Devkant Sen2 , Abhishek Bhatt3

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-9 , Page no. 162-166, Sep-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i9.162166

Online published on Sep 30, 2019

Copyright © Rukmani Kushwaha, Devkant Sen, Abhishek Bhatt . 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: Rukmani Kushwaha, Devkant Sen, Abhishek Bhatt, “Automated Cancer Diagnosis Identification System using Image Segmentation and Threshold Filter,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.9, pp.162-166, 2019.

MLA Style Citation: Rukmani Kushwaha, Devkant Sen, Abhishek Bhatt "Automated Cancer Diagnosis Identification System using Image Segmentation and Threshold Filter." International Journal of Computer Sciences and Engineering 7.9 (2019): 162-166.

APA Style Citation: Rukmani Kushwaha, Devkant Sen, Abhishek Bhatt, (2019). Automated Cancer Diagnosis Identification System using Image Segmentation and Threshold Filter. International Journal of Computer Sciences and Engineering, 7(9), 162-166.

BibTex Style Citation:
@article{Kushwaha_2019,
author = {Rukmani Kushwaha, Devkant Sen, Abhishek Bhatt},
title = {Automated Cancer Diagnosis Identification System using Image Segmentation and Threshold Filter},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {9 2019},
volume = {7},
Issue = {9},
month = {9},
year = {2019},
issn = {2347-2693},
pages = {162-166},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4868},
doi = {https://doi.org/10.26438/ijcse/v7i9.162166}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i9.162166}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4868
TI - Automated Cancer Diagnosis Identification System using Image Segmentation and Threshold Filter
T2 - International Journal of Computer Sciences and Engineering
AU - Rukmani Kushwaha, Devkant Sen, Abhishek Bhatt
PY - 2019
DA - 2019/09/30
PB - IJCSE, Indore, INDIA
SP - 162-166
IS - 9
VL - 7
SN - 2347-2693
ER -

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Abstract

In this postulation, some progress area based division approaches have created to perform picture division for grayscale and shading pictures. PC vision and picture getting applications, picture division is a significant pre-handling step. The fundamental objective of the division procedure is the partition of forefront area from foundation district. In light of the yield of the division result, division can be ordered as worldwide division or neighborhood division. The worldwide division goes for complete detachment of the article from the foundation while the neighborhood division partitions the picture into constituent locales. For accomplishing division, various calculations are created by different specialists. The division approaches are application explicit and don`t function admirably for both grayscale and shading picture division. For any picture comprising of frontal area and foundation, some change districts exist between the forefront and foundation areas. Powerful extraction of change district prompts a superior division result. In this manner, the doctoral postulation plans to proficient and viable change area approaches for picture division for both grayscale and shading pictures.

Key-Words / Index Term

Image Segmentation, ME, FPR, FNR

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