An Automatic Algorithm for Stitching Multi-Sequence Retinal Images

图像拼接 序列(生物学) 计算机科学 算法 人工智能 计算机视觉 生物 遗传学
作者
Yang Han,Zhensheng Gu,Baicheng Li,Chunbo Wu,Lingling Chen,Yuan Liu
出处
期刊:Social Science Research Network [Social Science Electronic Publishing]
标识
DOI:10.2139/ssrn.4188695
摘要

Background and Objective: Registration of retinal color fundus images which were taken at different times, from different perspectives is a critical prerequisite for diagnosis of retinopathy or other eye diseases. For the sake of automatic stitching of multiple retinal images, which can improve the speed of image registration while ensuring the accuracy of matching, a novel automatic registration algorithm of stitching multi-sequence retinal image is proposed in the essay. Methods: The method based on SURT algorithm segments retinal images into small regions, where the area is independent of each other, and then extracts saliency features. The geometric relationship between the sequence retinal image and the reference sequence image is then estimated from the offset which was been calculated from the matched feature point pairs via MODE algorithm. Finally, we use the maximum value fusion to obtain precise fusion image seamlessly. The main innovation of this algorithm is that it is an available avenue for stitching retinal color fundus from multimodality automatically with high speed and accuracy, without the need to adjust parameters. Results: Some experiments demonstrate that the method is highly accurate image stitching, with significantly solved the errors caused by the limitation of the splicing sequence and the accumulation of splicing errors. And the results indicate that the novel algorithm outperforms on private and public medical image database.
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