Segmentation fusion based on neighboring information for MR brain images
Multimedia Tools and Applications, ISSN: 1573-7721, Vol: 76, Issue: 22, Page: 23139-23161
2017
- 19Citations
- 8Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
In this paper, we study on how to boost image segmentation algorithms. First of all, a novel fusion scheme is proposed to combine different segmentations with mutual information to reduce misclassified pixels and obtain an accurate segmentation. As the class label of each pixel depends on the pixel’s gray level and neighbors’ labels, the fusion scheme takes both spatial and intensity information of pixels into account. Then, a detail thresholding segmentation case is designed using the proposed fusion scheme. In the case, the local Laplacian filter is used to get the smoothed version of original image. To accelerate segmentation, a discrete curve evolution based Otsu method is employed to segment the original image and its smoothed version to get two different segmentation maps. The fusion scheme is used to fuse the two maps to get the final segmentation result. Experiments on medical MR-T2 brain images are conducted to demonstrate the effectiveness of the proposed segmentation fusion method. The experimental results indicate that the proposed algorithm can improve segmentation accuracy and it is superior to other multilevel thresholding methods.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84994424644&origin=inward; http://dx.doi.org/10.1007/s11042-016-4098-3; http://link.springer.com/10.1007/s11042-016-4098-3; http://link.springer.com/content/pdf/10.1007/s11042-016-4098-3.pdf; http://link.springer.com/article/10.1007/s11042-016-4098-3/fulltext.html; https://dx.doi.org/10.1007/s11042-016-4098-3; https://link.springer.com/article/10.1007/s11042-016-4098-3
Springer Nature
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