Local mesh patterns for medical image segmentation
DOI:
https://doi.org/10.21276/apjhs.2018.5.1.29Keywords:
Local binary patterns, medical image segmentation, textureAbstract
In this paper, local mesh patterns (LMeP) feature extractor is proposed for medical image segmentation. The local region of image is represented by LMeP, which are evaluated by taking into consideration the magnitude of the local difference between the center pixel and its neighbors. First, image split into subblocks and LMeP features are extracted from each subblock. Once the image has been split into blocks of roughly homogeneous texture, we apply an agglomerative procedure to merge similar adjacent regions until one of the two stopping criteria is satis1ed. At each stage, we merge the pair of adjacent regions which have the largest merger importance (MI) value. Based on MI the regions are merged and then form the segmented regions for medical image segmentation application. Experimental results are tested on benchmark magnetic resonance image database for medical image segmentation application. Results after being investigated, proposed method shows a significant improvement for segmentation of images.
Downloads
Downloads
Published
How to Cite
Issue
Section
License
Asian Pacific Journal of Health Sciences applies the Creative Commons Attribution (CC-BY) license to published articles. Under this license, authors retain ownership of the copyright for their content, but they allow anyone to download, reuse, reprint, modify, distribute and/or copy the content as long as the original authors and source are cited. Appropriate attribution can be provided by simply citing the original article.