Volume 8 Issue 2 - March 2017

  • 1. Medical image analysis using multiresolution fusion techniques

    Authors : Kalyani Kapula, P. Bhavani Sankar

    Pages : 41-50

    DOI : http://dx.doi.org/10.21172/1.82.007

    Keywords : Image Fusion, PCA, LUT, FPGA, Optimal filter, etc.

    Abstract :

    In severe situations like accidents occur, majority of registered cases are for bone or head injury. For proper diagnosis, both CT scan and MRI scan are required to study the damage occurred for skull as well as for the internal organ injury of brain for the development of any brain tumors. If a combination of both images is present in a single image, then diagnosing the patient would be easier. Image Fusion is a method used to combine two input images to generate a combined complementary information contained image. For medical image processing, the resultant image is required to be highly reliable, low cost in terms of storage cost, uncertainty, etc. Also the information in both CT scan and MRI scan must be retained in the fused image for reliable study and assessment for diagnosis. This paper deals with pixel level fusion methods and their generic multiresolution fusion scheme. This scheme utilizes the low pass residuals and high pass residuals to segregate the information of two input images that are to be fused. The linear and nonlinear methods are used to develop the fused image. The fused image is evaluated in terms of fusion metrics such as standard deviation, entropy, fusion mutual information, etc. The methods like laplacian pyramid, ratio pyramid, principal component analysis, average methods prove to be better options for medical image fusion.

    Citing this Journal Article :

    Kalyani Kapula, P. Bhavani Sankar, "Medical image analysis using multiresolution fusion techniques", https://www.ijltet.org/journal_details.php?id=911&j_id=3656, Volume 8 Issue 2 - March 2017, 41-50, #ijltetorg