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Prediction of Survival of Glioblastoma Patients Using Local Spatial Relationships and Global Structure Awareness in FLAIR MRI Brain Images | IEEE Journals & Magazine | IEEE Xplore

Prediction of Survival of Glioblastoma Patients Using Local Spatial Relationships and Global Structure Awareness in FLAIR MRI Brain Images


The architecture of the proposed method. Our approach includes three steps: The first step is tumor segmentation, The second is learning the local spatial relationships, ...

Abstract:

This article introduces a framework for predicting the survival of brain tumor patients by analyzing magnetic resonance images. The prediction of brain tumor survival is ...Show More

Abstract:

This article introduces a framework for predicting the survival of brain tumor patients by analyzing magnetic resonance images. The prediction of brain tumor survival is challenging due to the limited size of available datasets. To overcome the issue of overfitting, we propose a self-supervised learning method that involves identifying image patches from the same or different images. By recognizing intra- and inter-image differences, the network can learn the relationships between local spatial windows in the same image and across different images. In addition to analyzing local information, we also incorporate a global structure awareness network to capture global information from the entire image. Our proposed method shows a strong correlation between local spatial relationships and survivor class prediction in FLAIR MRI brain images. We evaluate our method using the BraTS 2020 validation dataset and observe that our method outperforms others in accuracy and SpearmanR correlation metrics.
The architecture of the proposed method. Our approach includes three steps: The first step is tumor segmentation, The second is learning the local spatial relationships, ...
Published in: IEEE Access ( Volume: 11)
Page(s): 37437 - 37449
Date of Publication: 13 April 2023
Electronic ISSN: 2169-3536

Funding Agency:


References

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