[HTML][HTML] Reproducible and interpretable machine learning-based radiomic analysis for overall survival prediction in glioblastoma multiforme
Simple Summary This study aimed to develop and validate a radiomic model for predicting
overall survival (OS) in glioblastoma multiforme (GBM) patients using pre-treatment MRI …
overall survival (OS) in glioblastoma multiforme (GBM) patients using pre-treatment MRI …
Modified U-Net with attention gate for enhanced automated brain tumor segmentation
This study addresses the formidable challenges encountered in automated brain tumor
segmentation, including the complexities of irregular shapes, ambiguous boundaries, and …
segmentation, including the complexities of irregular shapes, ambiguous boundaries, and …
Advancing Brain Tumor Segmentation with Spectral–Spatial Graph Neural Networks
S Mohammadi, M Allali - Applied Sciences, 2024 - mdpi.com
In the field of brain tumor segmentation, accurately capturing the complexities of tumor sub-
regions poses significant challenges. Traditional segmentation methods usually fail to …
regions poses significant challenges. Traditional segmentation methods usually fail to …
Distance Analysis and Dimensionality Reduction using PCA on Brain Tumour MRI Scans
A Jhariya, D Parekh, J Lobo, A Bongale… - … on Pervasive Health …, 2024 - publications.eai.eu
INTRODUCTION: Compression of MRI images while maintaining essential information,
makes it easier to distinguish between different types of brain tumors. It also assesses the …
makes it easier to distinguish between different types of brain tumors. It also assesses the …