[HTML][HTML] Improved Brain Tumor Segmentation in MR Images with a Modified U-Net
Detecting brain tumors is crucial in medical diagnostics due to the serious health risks these
abnormalities present to patients. Deep learning approaches can significantly improve …
abnormalities present to patients. Deep learning approaches can significantly improve …
GETNet: Group Normalization Shuffle and Enhanced Channel Self-Attention Network Based on VT-UNet for Brain Tumor Segmentation
B Guo, N Cao, R Zhang, P Yang - Diagnostics, 2024 - mdpi.com
Currently, brain tumors are extremely harmful and prevalent. Deep learning technologies,
including CNNs, UNet, and Transformer, have been applied in brain tumor segmentation for …
including CNNs, UNet, and Transformer, have been applied in brain tumor segmentation for …
TDPC-Net: Multi-scale lightweight and efficient 3D segmentation network with a 3D attention mechanism for brain tumor segmentation
Y Li, J Kang - Biomedical Signal Processing and Control, 2025 - Elsevier
Accurate identification and segmentation of brain tumors from multimodal MRI images is
essential for making treatment decisions and planning surgeries. However, the complexity …
essential for making treatment decisions and planning surgeries. However, the complexity …
Data Augmentation using Spatial Transformation for Brain Tumor Segmentation Improvement
EK Susanto, H Tjandrasa… - … International Seminar on …, 2024 - ieeexplore.ieee.org
Manual segmentation of MRI images, which is important for ultimately improving patient
outcomes, is time-consuming, prone to error, and heavily dependent on the expertise of …
outcomes, is time-consuming, prone to error, and heavily dependent on the expertise of …
Enhancing Brain Tumor MRI Segmentation Accuracy and Efficiency with Optimized U-Net Architecture
SA Hamim, AI Jony - Malaysian Journal of Science and Advanced …, 2024 - mjsat.com.my
This study presents an enhanced approach to brain tumor segmentation using an optimized
U-Net architecture, focusing on MRI scans. Our research proposes an automated solution …
U-Net architecture, focusing on MRI scans. Our research proposes an automated solution …