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To Achieve Software Quality Assurance in Brain Tumor Detection Using Artificial Neural Networks

V. Praba1 , S. Sivakumar2

  1. Department of Computer Science, Thanthai Hans Roever College, Perambalur, India.
  2. Department of Computer Science, Thanthai Hans Roever College, Perambalur, India.

Correspondence should be addressed to: prabamca2014@gmail.com.

Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-10 , Page no. 118-121, Oct-2017

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v5i10.118121

Online published on Oct 30, 2017

Copyright © V. Praba, S. Sivakumar . 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: V. Praba, S. Sivakumar, “To Achieve Software Quality Assurance in Brain Tumor Detection Using Artificial Neural Networks,” International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.118-121, 2017.

MLA Style Citation: V. Praba, S. Sivakumar "To Achieve Software Quality Assurance in Brain Tumor Detection Using Artificial Neural Networks." International Journal of Computer Sciences and Engineering 5.10 (2017): 118-121.

APA Style Citation: V. Praba, S. Sivakumar, (2017). To Achieve Software Quality Assurance in Brain Tumor Detection Using Artificial Neural Networks. International Journal of Computer Sciences and Engineering, 5(10), 118-121.

BibTex Style Citation:
@article{Praba_2017,
author = {V. Praba, S. Sivakumar},
title = {To Achieve Software Quality Assurance in Brain Tumor Detection Using Artificial Neural Networks},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {10 2017},
volume = {5},
Issue = {10},
month = {10},
year = {2017},
issn = {2347-2693},
pages = {118-121},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1485},
doi = {https://doi.org/10.26438/ijcse/v5i10.118121}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v5i10.118121}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1485
TI - To Achieve Software Quality Assurance in Brain Tumor Detection Using Artificial Neural Networks
T2 - International Journal of Computer Sciences and Engineering
AU - V. Praba, S. Sivakumar
PY - 2017
DA - 2017/10/30
PB - IJCSE, Indore, INDIA
SP - 118-121
IS - 10
VL - 5
SN - 2347-2693
ER -

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Abstract

Quality assurance is a way of preventing errors and avoiding problems when distributing software to clients. The term quality assurance is refers to ways of ensuring the quality of a product. Here we detect the brain tumor detection with segmentation using genetic algorithm and testing that application output by ANN. Brain is the central nervous system of a human being one of the major causes of death among people is brain tumor. In medical field like this kind of causes are struggling to detect automatically with quality. Here provided solution to detect the tumor automatically the same way testing the automated output by ANN for improving the quality of software. Proposed method integrates image pre-processing, future extraction, segmentation, classification and testing.

Key-Words / Index Term

Quality assurance,Artificial Nural Networks,Pre-processing,Segmantation,Feture extraction,Classification,testing

References

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