Advancements in glioma segmentation: comparing the U-Net and DeconvNet models
In this study, we address the challenge of accurately segmenting gliomas from magnetic resonance imaging (MRI) scans, an essential task for treatment planning and prognosis in glioma patients. Prompted by the limitations of manual segmentation methods and the need for precise automated techniques, t...
| Main Authors: | , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Journal of Emerging Investigators, Inc
2024
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