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An Interval Iteration Based Multilevel Thresholding Algorithm for Brain MR Image Segmentation.

Authors :
Feng, Yuncong
Liu, Wanru
Zhang, Xiaoli
Liu, Zhicheng
Liu, Yunfei
Wang, Guishen
Source :
Entropy. Nov2021, Vol. 23 Issue 11, p1429. 1p.
Publication Year :
2021

Abstract

In this paper, we propose an interval iteration multilevel thresholding method (IIMT). This approach is based on the Otsu method but iteratively searches for sub-regions of the image to achieve segmentation, rather than processing the full image as a whole region. Then, a novel multilevel thresholding framework based on IIMT for brain MR image segmentation is proposed. In this framework, the original image is first decomposed using a hybrid L1 − L0 layer decomposition method to obtain the base layer. Second, we use IIMT to segment both the original image and its base layer. Finally, the two segmentation results are integrated by a fusion scheme to obtain a more refined and accurate segmentation result. Experimental results showed that our proposed algorithm is effective, and outperforms the standard Otsu-based and other optimization-based segmentation methods. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10994300
Volume :
23
Issue :
11
Database :
Academic Search Index
Journal :
Entropy
Publication Type :
Academic Journal
Accession number :
153872988
Full Text :
https://doi.org/10.3390/e23111429