Edge Preserving Multi-Modal Registration Based On Gradient Intensity Self-Similarity

被引：0
|
作者：
Rott, Tamar [1 ]
Shriki, Dorin [1 ]
Bendory, Tamir [1 ]
机构：
[1] Technion Israel Inst Technol, Dept Elect Engn, IL-32000 Haifa, Israel
来源：
2014 IEEE 28TH CONVENTION OF ELECTRICAL & ELECTRONICS ENGINEERS IN ISRAEL (IEEEI) | 2014年
关键词：
Image registration; multi-modal similarity metric; self-similarity; image gradient; IMAGE REGISTRATION;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Image registration is a challenging task in the world of medical imaging. Particularly, accurate edge registration plays a central role in a variety of clinical conditions. The Modality Independent Neighbourhood Descriptor (MIND) demonstrates state of the art alignment, based on the image self-similarity. However, this method appears to be less accurate regarding edge registration. In this work, we propose a new registration method, incorporating gradient intensity and MIND self-similarity metric. Experimental results show the superiority of this method in edge registration tasks, while preserving the original MIND performance for other image features and textures.
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页数：5
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