5 citations · 6 across the 3 of their papers we have counts for
3 papers
An Efficient Dual-Line Decoder Network with Multi-Scale Convolutional Attention for Multi-organ Segmentation
Riad Hassan, M. Rubaiyat Hossain Mondal, Sheikh Iqbal Ahamed +2
Proper segmentation of organs-at-risk is important for radiation therapy, surgical planning, and diagnostic decision-making in medical image analysis. While deep learning-based seg…
Size and Smoothness Aware Adaptive Focal Loss for Small Tumor Segmentation
Md Rakibul Islam, Riad Hassan, Abdullah Nazib +3
Deep learning has achieved remarkable accuracy in medical image segmentation, particularly for larger structures with well-defined boundaries. However, its effectiveness can be cha…
Uncertainty Driven Bottleneck Attention U-net for Organ at Risk Segmentation
Abdullah Nazib, Riad Hassan, Zahidul Islam +1
Organ at risk (OAR) segmentation in computed tomography (CT) imagery is a difficult task for automated segmentation methods and can be crucial for downstream radiation treatment pl…