文档介绍：Abstract
Abstract
Multimodality medical image fusion refers to bination of medical images with different modalities,aiming at fully indicating the advantage the morphological imaging method h弱of t11e high resolution and accurate location,ing the disadvantage of the low definition in spatial resolution and tissue contrast resolution existing in functional imaging,excavating imaging information to the utmost,and
obtaining more information SO as to understand prehensive information of the
diseased tissues ans,thus providing reliable basis for doctors to make an accurate diagnosis or appropriate treatment a wide application prospect,the medical image fusion has currently e a hotspot in medical image processing. Multimodality medical image fusion iS studied in this paper.
Aiming at the loss of palt of edges and the blur of textures in medical image fusion
metllod which is based on wavelet transform,the method based on multiwavelet transform and fuzzy reasoning is proposed,which uses the multiwavelet pact support,symmetry and high vanish square to provide a more accurate multi-resolution analysis space for the analysis of and parison between different multiwavelet,the multiwavelet fusion operator most suitable for medical image fusion iS the design of fusion rules,in high·ponents rules based on fuzzy reasoning are multiwavelet coefficients in high—frequency domain al e
mapped into fuzzy sets SO as to effectively avoid the ambiguity in the fusion low-ponents,regional weighted variance rules are experiment results show that the proposed method call adequately keep the source image information and has a better fusion performance than wavelets-based fusion method.
(Dempster-Shafer)evidence theory has currently been essfully applied to of data fusion。risk assessment and surface this paper,D—S
evidence theory is introduced into the multimodality medical image fusion firstly,and