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PBTNet: A New Computer-Aided Diagnosis System for Detecting Primary Brain Tumors

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journal contribution
posted on 18.11.2022, 16:51 authored by SY Lu, SC Satapathy, SH Wang, YD Zhang
Brain tumors are among the leading human killers. There are over 120 different types of brain tumors, but they mainly fall into two groups: primary brain tumors and metastatic brain tumors. Primary brain tumors develop from normal brain cells. Early and accurate detection of primary brain tumors is vital for the treatment of this disease. Magnetic resonance imaging is the most common method to diagnose brain diseases, but the manual interpretation of the images suffers from high inter-observer variance. In this paper, we presented a new computer-aided diagnosis system named PBTNet for detecting primary brain tumors in magnetic resonance images. A pre-trained ResNet-18 was selected as the backbone model in our PBTNet, but it was fine-tuned only for feature extraction. Then, three randomized neural networks, Schmidt neural network, random vector functional-link, and extreme learning machine served as the classifiers in the PBTNet, which were trained with the features and their labels. The final predictions of the PBTNet were generated by the ensemble of the outputs from the three classifiers. 5-fold cross-validation was employed to evaluate the classification performance of the PBTNet, and experimental results demonstrated that the proposed PBTNet was an effective tool for the diagnosis of primary brain tumors.

Funding

This Study was partially supported by Hope Foundation for Cancer Research, United Kingdom (RM60G0680), Royal Society International Exchanges Cost Share Award, United Kingdom (RP202G0230), Medical Research Council Confidence in Concept Award, United Kingdom (MC_PC_17171), British Heart Foundation Accelerator Award, United Kingdom (AA/18/3/34220); Sino-UK Industrial Fund, United Kingdom (RP202G0289); Global Challenges Research Fund (GCRF), United Kingdom (P202PF11). S-YL holds the CSC scholarship with University of Leicester.

History

Citation

Lu S-Y, Satapathy SC, Wang S-H and Zhang Y-D (2021) PBTNet: A New Computer-Aided Diagnosis System for Detecting Primary Brain Tumors. Front. Cell Dev. Biol. 9:765654. doi: 10.3389/fcell.2021.765654

Author affiliation

School of Computing and Mathematical Sciences

Version

VoR (Version of Record)

Published in

Frontiers in Cell and Developmental Biology

Volume

9

Pagination

765654

Publisher

Frontiers Media SA

eissn

2296-634X

Acceptance date

27/09/2021

Copyright date

2021

Available date

18/11/2022

Language

en