A Novel Biomedical Image Classification Using Kernel Support Vector Machine

@article{1702207,
      author = {K. Leela Prasad, K. Ganga Eswar, Lokesh. G., K. Sai Krishna},
      title = {A Novel Biomedical Image Classification Using Kernel Support Vector Machine},
      journal = {Iconic Research And Engineering Journals},
      year = {2020},
      volume = {3},
      number = {10},
      pages = {173-177},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/17022071.pdf},
      abstract = {An accurate and automated type classification of MRI scan based brain images is more extremely important during medical analysis and interpretation of brain. From over past decade various methods have already been implemented. In this Project, we can use a novel method for the classification of a given MRI brain scan image as normal or abnormal. The proposed method that was first perform wavelet transform to extract original features from MRI scanned images, In next step we can apply principle component analysis in order to reduce the dimensions of features. Those features are submitted to a kernel support vector machine (KSVM) for classification of Brain Images for normal and abnormal. The strategy of K-fold stratified cross validation was used to enhance generalization of KSVM.},
      keywords = {Tumor, Digital Signal Processing, Matlab, Gesture MRI Scan, Vector Machine, Kernel},
      month = {April},
  }