The performance of different machine learning algorithms in the classification of gliomas is promising. An even better performance may be expected by integrating features extracted from other MR sequences.

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Most digital cameras use color filter arrays of different patterns to capture color image. The output of the color filter array is a sampled version of the original color image. Demosaicing algorithms are used to reconstruct the original color image from this sampled version. Medical image analysis is increasing day by day. The amount of data to be saved is also on the increase. Standard compression techniques like JPEG if used may cause loss of diagnostic data which cannot be tolerated. So if a proper demosaicing algorithm can be found such that there is not much loss of data in reconstruction then the images can be saved in raw format and color image can be reconstructed using this algorithm, when needed, leading to a great amount of compression. This paper studies and compares different existing demosaicing algorithms to find a suitable algorithm for this application.