Liver Lesions and Acute Intracerebral Hemorrhage Detection Using Multimodal Fusion

Medical image fusion is designed to help physicians in their decisions by providing them with a preclinical enough information. Accurate assessment and effective treatment of the disease reduce time it takes relieve symptoms disease. This article utilizes an data approach work on two different imaging modalities; computed tomography (CT) magnetic resonance (MRI). The based combination singular value decomposition (SVD) Fast Discrete Curvelet Transform (FDCT) techniques processing during process. SVD-FDCT being tested multimodal medical applications. first application concerns detection liver lesions second early acute intracerebral hemorrhage. Experimental tests demonstrate that not only algorithm can treat curved objects edges effectively as FDCT do. But also, throughput comparable related algorithms such principal component analysis (PCA), Wavelet (DWT), dual-tree complex wavelet transform (DT-CWT), algorithms.