A hybrid feature selection‐based approach for brain tumor detection and automatic segmentation on multiparametric magnetic resonance images-Reference-Cited by-同舟云学术

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A hybrid feature selection‐based approach for brain tumor detection and automatic segmentation on multiparametric magnetic resonance images

Published:2021-09-24 Issue:11 Volume:48 Page:6614-6626
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Medical Physics

Author:

Chen Hao¹²,Ban Duo¹,Qi X. Sharon³,Pan Xiaoying¹²,Qiang Yongqian⁴,Yang Qing⁵

Affiliation:

1. School of Computer Science and Technology Xi'an University of Posts and Telecommunications Xi'an China

2. Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi'an University of Posts and Telecommunications Xi’an China

3. Department of Radiation Oncology University of California Los Angeles Los Angeles California USA

4. First Affiliated Hospital of Xi’an Jiaotong University Xi’an China

5. School of Sport and Health Sciences Xi’an Physical Education University Xi’an China

Funder

National Natural Science Foundation of China

Natural Science Basic Research Program of Shaanxi Province

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.15026

Reference38 articles.

1. Computer-Aided Grading of Gliomas Combining Automatic Segmentation and Radiomics

2. 3D tumor detection in automated breast ultrasound using deep convolutional neural network

3. An expert system for brain tumor detection: Fuzzy C-means with super resolution and convolutional neural network with extreme learning machine

4. Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images

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1. Attention‐guided multi‐scale context aggregation network for multi‐modal brain glioma segmentation;Medical Physics;2023-05-07

2. Bio-Inspired Feature Selection in Brain Disease Detection via an Improved Sparrow Search Algorithm;IEEE Transactions on Instrumentation and Measurement;2023

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