PREDICTION OF LEUKAEMIA CANCER IMAGES USING PARALLEL SALIENCY ALGORITHM

Authors

  • SWARNALATHA P School of Computing Science & Engineering, VIT University, Vellore-14,India.
  • ANBARASI M. School of Computing Science & Engineering, VIT University, Vellore-14,India.
  • AMAN SHARMA School of Computing Science & Engineering, VIT University, Vellore-14,India.
  • GANESH M School of Computing Science & Engineering, VIT University, Vellore-14,India.

Keywords:

Parallel Saliency Algorithm, Leukemia Cancer Images, Saliency Map, Naive Bayes and Decision Tree

Abstract

Parallel Saliency algorithm is applied to solve the medical issues and to reduce the doctors’ work in the society.  Prediction of specific area of a leukemia, cancer image can be made using a Parallel Saliency algorithm (PSA).  Firstly, most affected phase of the leukemia cancer is possible by applying the parallel saliency algorithm over cancer images, secondly, PSA works in a multi-core environment in comparison with the existing saliency algorithm. As a whole, the paper deals with PSA, which provides efficient performance to researchers and scientist.

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Published

30.06.2015

How to Cite

SWARNALATHA P, ANBARASI M., AMAN SHARMA, & GANESH M. (2015). PREDICTION OF LEUKAEMIA CANCER IMAGES USING PARALLEL SALIENCY ALGORITHM. International Journal of Pharma and Bio Sciences, 6(2), 226–232. Retrieved from https://ijpbs.net/index.php/journal/article/view/4145

Issue

Volume 6, Issue 2, 2015

Section

Research Articles

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Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.