A novel extended Kalman filter with support vector machine based method for the automatic diagnosis and segmentation of brain tumors-Reference-Cited by-同舟云学术

A novel extended Kalman filter with support vector machine based method for the automatic diagnosis and segmentation of brain tumors

Published:2021-03 Issue: Volume:200 Page:105797
ISSN:0169-2607
Container-title:Computer Methods and Programs in Biomedicine
language:en
Short-container-title:Computer Methods and Programs in Biomedicine

Author:

Chen Baoshi,Zhang Lingling^ORCID,Chen Hongyan,Liang Kewei,Chen Xuzhu

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Beijing Municipal Science & Technology Commission

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications,Software

Reference34 articles.

1. A distinctive approach in brain tumor detection and classification using MRI;Amin;Pattern Recognit. Lett.,2017

2. An improved implementation of brain tumor detection using segmentation based on hierarchical self organizing map;Logeswari;Int. J. Comput. Theory Eng.,2010

3. Classification of brain tumor MRIs using a kernel support vector machine;Abd-Ellah,2016

4. An algorithm for detecting brain tumors in MRI images;Badran,2010

5. Brain tumor classification using mixed method approach;Bangare,2017

Cited by 40 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Multi-scale cross spectral coherence and phase spectral distribution based measurement in non-subsampled shearlet domain for classification of brain tumors;Expert Systems with Applications;2024-08

2. Advancements in traditional machine learning techniques for detection and diagnosis of fatal cancer types: Comprehensive review of biomedical imaging datasets;Measurement;2024-02

3. An efficient method for MRI brain tumor tissue segmentation and classification using an optimized support vector machine;Multimedia Tools and Applications;2024-01-29

4. Magnetic resonance imaging-based brain tumor image classification performance enhancement;Scientific African;2023-11

5. Deep learning‐based robust hybrid approaches for brain tumor classification in magnetic resonance images;International Journal of Imaging Systems and Technology;2023-10-10