Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (1)
  • Open Access


    Brain Tumour Detection by Gamma DeNoised Wavelet Segmented Entropy Classifier

    Simy Mary Kurian1, Sujitha Juliet Devaraj1,*, Vinodh P. Vijayan2

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2093-2109, 2021, DOI:10.32604/cmc.2021.018090

    Abstract Magnetic resonance imaging (MRI) is an essential tool for detecting brain tumours. However, identification of brain tumours in the early stages is a very complex task since MRI images are susceptible to noise and other environmental obstructions. In order to overcome these problems, a Gamma MAP denoised Strömberg wavelet segmentation based on a maximum entropy classifier (GMDSWS-MEC) model is developed for efficient tumour detection with high accuracy and low time consumption. The GMDSWS-MEC model performs three steps, namely pre-processing, segmentation, and classification. Within the GMDSWS-MEC model, the Gamma MAP filter performs the pre-processing task and achieves a significant increase in… More >

Displaying 1-10 on page 1 of 1. Per Page