Recent deep learning-based brain tumor segmentation models using multi-modality magnetic resonance imaging: a prospective survey
Radiologists encounter significant challenges when segmenting and determining brain
tumors in patients because this information assists in treatment planning. The utilization of …
tumors in patients because this information assists in treatment planning. The utilization of …
SARFNet: Selective Layer and Axial Receptive Field Network for Multimodal Brain Tumor Segmentation
B Guo, N Cao, P Yang, R Zhang - Applied Sciences, 2024 - mdpi.com
Efficient magnetic resonance imaging (MRI) segmentation, which is helpful for treatment
planning, is essential for identifying brain tumors from detailed images. In recent years …
planning, is essential for identifying brain tumors from detailed images. In recent years …
SSGNet: Selective Multi-Scale Receptive Field and Kernel Self-Attention Based on Group-Wise Modality for Brain Tumor Segmentation
B Guo, N Cao, P Yang, R Zhang - Electronics, 2024 - mdpi.com
Medical image processing has been used in medical image analysis for many years and
has achieved great success. However, one challenge is that medical image processing …
has achieved great success. However, one challenge is that medical image processing …