Detection of Masses in Mammograms using Bayesian Method and Machine learning

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    Every 100th cases in cancer we come across are of breasts cancer cases. It is becoming very common in woman of all ages. Correct detection of these lesions in breast is very important. With less of human intervention, the goal is to do the correct diagnosis. Not all the cases of breast masses are futile. If the cases are not dealt properly, they might create panic amongst people. Human detection without machine intervention is not hundred percent accurate. If machines can be deeply trained, they can do the same work of detection with much more accuracy. Bayesian method has a vast area of application in the field of medical image processing as well as in machine learning. This paper intends to use Bayesian probabilistic in image segmentation as well as in machine learning. Machine learning in image processing means application in pattern recognition. There are various machine learning algorithms that can classify an image at their best. In the proposed system, we will be firstly segment the image using Bayesian method. On the segmented parts of the image, we will be applying machine learning algorithm to diagnose the mass or the growth.

     

     


  • Keywords


    masses in mammograms, Bayesian method, machine learning.

  • References


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Article ID: 20441
 
DOI: 10.14419/ijet.v7i4.6.20441




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