A modified threshold score‐based multilevel thresholding segmentation technique for brain magnetic resonance images using opposition‐based learning hybrid rice optimization algorithm-Reference-Cited by-同舟云学术

A modified threshold score‐based multilevel thresholding segmentation technique for brain magnetic resonance images using opposition‐based learning hybrid rice optimization algorithm

Published:2022-11-25 Issue:2 Volume:33 Page:622-643
ISSN:0899-9457
Container-title:International Journal of Imaging Systems and Technology
language:en
Short-container-title:Int J Imaging Syst Tech

Author:

Ye Zhiwei¹,Song Zilun¹^ORCID,Li Pengfei¹,Wang Mingwei¹,Hou Wenguang²

Affiliation:

1. School of Computer Science Hubei University of Technology Wuhan China

2. College of Life Science and Technology Huazhong University of Science and Technology Wuhan China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Software,Electronic, Optical and Magnetic Materials

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ima.22830

Reference50 articles.

1. Moving Medical Image Analysis to GPU Embedded Systems: Application to Brain Tumor Segmentation

2. NeXt for neuro-radiosurgery: A fully automatic approach for necrosis extraction in brain tumor MRI using an unsupervised machine learning technique

3. Brightness preserving optimized weighted bi‐histogram equalization algorithm and its application to MR brain image segmentation

4. Automated brain tumor segmentation on multi-modal MR image using SegNet

5. MRI brain tumor detection using optimal possibilistic fuzzy C-means clustering algorithm and adaptive k-nearest neighbor classifier

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