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Enhanced Model for Fusion of Multi-Modality Images: Discrete Wavelet Transformation using Region based Fusion Rules - Softcover
Inhaltsangabe
Medical Image Fusion has been used to derive the useful information from multimodality medical image data. The idea is to improve the image content by fusing images like CT and MRI image, so as to improve more information to the doctor and clinical treatment planning system. Despite the significant research conducted on this topic and many algorithms have been developed for the image fusion, but the development of an efficient image fusion method is still a big challenge for the researchers. In the Present work, New Efficient Method is proposed for Image Fusion. The proposed method is developed using Discrete Wavelet Transform and it involves region based fusion rules to optimize the image pixel values to be fused togather. The proposed method is compared with both qualitatively as well as quantitatively with the other fusion methods. After that the resultant images are validated using Phantom Images as well as Clinical Testing. The Experimental results show that the proposed method is better than other multi model image fusion methods and increases the contrast of the fused image thereby preserving the detail features.
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Reseña del editor
Medical Image Fusion has been used to derive the useful information from multimodality medical image data. The idea is to improve the image content by fusing images like CT and MRI image, so as to improve more information to the doctor and clinical treatment planning system. Despite the significant research conducted on this topic and many algorithms have been developed for the image fusion, but the development of an efficient image fusion method is still a big challenge for the researchers. In the Present work, New Efficient Method is proposed for Image Fusion. The proposed method is developed using Discrete Wavelet Transform and it involves region based fusion rules to optimize the image pixel values to be fused togather. The proposed method is compared with both qualitatively as well as quantitatively with the other fusion methods. After that the resultant images are validated using Phantom Images as well as Clinical Testing. The Experimental results show that the proposed method is better than other multi model image fusion methods and increases the contrast of the fused image thereby preserving the detail features.
Biografía del autor
Er. Pankaj Bhambri graduated from Dr. B.R.Ambedkar University, Agra with B.E.(IT) HONORS in 2003. He Completed his M.Tech. (CSE) from P.T.U., Jalandhar at Guru Nanak Dev Engineering College, Ludhiana. His interest areas are Bioinformatics, Image Processing and Distributed Computing.He had received "Best Teacher Award" & "Distiguished Alumni Award".
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Enhanced Model for Fusion of Multi-Modality Images
Verlag:
LAP LAMBERT Academic Publishing Aug 2012, 2012
ISBN 10: 3659208086
ISBN 13: 9783659208089
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Taschenbuch. Zustand: Neu. Neuware -Medical Image Fusion has been used to derive the useful information from multimodality medical image data. The idea is to improve the image content by fusing images like CT and MRI image, so as to improve more information to the doctor and clinical treatment planning system. Despite the significant research conducted on this topic and many algorithms have been developed for the image fusion, but the development of an efficient image fusion method is still a big challenge for the researchers. In the Present work, New Efficient Method is proposed for Image Fusion. The proposed method is developed using Discrete Wavelet Transform and it involves region based fusion rules to optimize the image pixel values to be fused togather. The proposed method is compared with both qualitatively as well as quantitatively with the other fusion methods. After that the resultant images are validated using Phantom Images as well as Clinical Testing. The Experimental results show that the proposed method is better than other multi model image fusion methods and increases the contrast of the fused image thereby preserving the detail features.Books on Demand GmbH, Überseering 33, 22297 Hamburg 68 pp. Englisch. Artikel-Nr. 9783659208089
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