Analysis and Identification of Tumor Cells In MRI And CT Images Based On Nanotechnology Using Neuro Fuzzy Image Fusion

Image fusion is a sub field of Medical imaging in which more than one images are fused to create an image where all the objects are in focus. The process of image fusion is performed for multi-sensor and multi-focus images of the same scene. Multi-sensor images of the same scene are captured by different sensors whereas multi-focus images are captured by the same sensor. In multi-focus images, the objects in the scene which are closer to the camera are in focus and the farther objects get blurred. Contrary to it, when the farther objects are focused then closer objects get blurred in the image. To achieve an image where all the objects are in focus, the process of images fusion is performed either in spatial domain or in transformed domain. In recent times, the applications of image processing have grown immensely. Usually due to limited depth of field of optical lenses especially with greater focal length, it becomes impossible to obtain an image where all the objects are in focus. Thus it plays an important role to perform tasks of analysis and identification of tumor cells in MRI and CT images based on neuro fuzzy image fusion. Hence, a novel feature-level multi-focus image fusion technique has been proposed which fuses multi-focus images. Thus the results of extensive experimentation performed to highlight the efficiency and utility of the proposed technique is presented. The proposed work further explores comparison between fuzzy based image fusion and neuro fuzzy fusion technique along with quality evaluation indices. In order to benefit from the highly conformal irradiation of, sophisticated treatment planning and simulation are required to analysis and identify the tumor in MRI and CT Scan images. The purpose of this study was to investigate the potential of MRI and CT for treatment plan simulation and adaptation using a neuro fuzzy image fusion.