Markov Clustering Based Feature Selection for Brain Tumor Segmentation from Multi-Spectral MRI Records-Reference-Cited by-同舟云学术

Markov Clustering Based Feature Selection for Brain Tumor Segmentation from Multi-Spectral MRI Records

Published:2022-03-02 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 20th Jubilee World Symposium on Applied Machine Intelligence and Informatics (SAMI)
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Author:

Pisak-Lukats Ioan-Marius¹,Szilagyi Laszlo²

Affiliation:

1. Sapientia University,Tîrgu Mureş,Romania

2. Sapientia University,Computational Intelligence Research Group,Tîrgu Mureş,Romania

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9780659/9780666/09780855.pdf?arnumber=9780855

Reference17 articles.

1. A feature ranking and selection algorithm for brain tumor segmentation in multi-spectral magnetic resonance image data;gy?rfi;IEEE Engineering Medicine and Biology Society (EMBC) Annual Int Conf,2019

2. Low and high grade glioma segmentation in multispectral brain MRI data

3. Binary Decision Diagrams

4. A fully automatic procedure´ for brain tumor segmentation from multi-spectral MRI records using ensemble learning and atlas-based data enhancement;gy?rfi;Applied Sciences,2021

5. New variants of a method of MRI scale standardization

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1. A feature selection strategy using Markov clustering, for the optimization of brain tumor segmentation from MRI data;Acta Universitatis Sapientiae, Informatica;2022-12-01

2. A two-stage U-net approach to brain tumor segmentation from multi-spectral MRI records;Acta Universitatis Sapientiae, Informatica;2022-12-01