Medical Image Analysis using Machine Learning Techniques

Authors

  • Kumar SR Department of Computer Science, EWIT ,Bangalore, India
  • Kumar N Department of Computer Science, EWIT ,Bangalore, India
  • Dubey GM Department of Computer Science, EWIT ,Bangalore, India
  • Rajshekhar SA Department of Computer Science, EWIT ,Bangalore, India

Keywords:

OpenCV, Image Processing,, Active contour, Machine Learning, Segmentation, Feature Extraction

Abstract

Image Processing has been a growing field for the biomedical images. MRI, CT scans and X-Ray are the different types ofimages used in this technique. All these techniques helps to identify even a minute deformity in the human body. The main purpose of medical image processing is to extract meaningful information from these images. MRI is the most reliable form of biomedical image available to us asit does not expose the human body to any sorts of harmful radiation. Once the MRI is obtained it can be processed, and the part of brain affected by tumor can be segmented. The complete process of detecting brain tumor from an MRI can be classified into four different categories: Pre-Processing, Segmentation,Feature Extraction and Tumor Detection. This survey involves analyzing and taking help of the research by other professionals and compiling it into one paper.

References

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Published

2025-11-26

How to Cite

[1]
S. R. Kumar, N. Kumar, G. M. Dubey, and R. SA, “Medical Image Analysis using Machine Learning Techniques”, Int. J. Comp. Sci. Eng., vol. 7, no. 15, pp. 159–164, Nov. 2025.

Issue

Vol. 7 No. 15 (2019): IJCSE Special Issue May Edition

Section

Research Article

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