Analysis of breast cancer cell based on hyperchromatic crowded group using multiple techniques of data mining

Chayanika Sarmah

Abstract


In this paper, an effort is made to analyze MGG stain images of breast cell in FNAC which will help in early detection of malignant breast cancer cell. There are many morphological features based on which MGG stain test smear images can be categorized into normal and abnormal classes. Some of them are area, perimeter and presence of hyperchromatic crowded (HCG) group etc. So, in this approach we analyse the breast cell based on a presence in the malignant cell using multiple techniques of data mining (Images are examined). The proposed approach is implemented in WEKA, a java based data mining tool

KEYWORDS: breast cancer, HCG, MGG, FNAC.


Full Text:

PDF


DOI: https://doi.org/10.23956/ijarcsse.v8i10.871

Refbacks

  • There are currently no refbacks.




© International Journals of Advanced Research in Computer Science and Software Engineering (IJARCSSE)| All Rights Reserved | Powered by Advance Academic Publisher.