2 citations · 2 across the 1 of their papers we have counts for
3 papers
eess.IV2026
Skill-Evolving Grounded Reasoning for Free-Text Promptable 3D Medical Image Segmentation
Tongrui Zhang, Chenhui Wang, Yongming Li +3
Free-text promptable 3D medical image segmentation offers an intuitive and clinically flexible interaction paradigm. However, current methods are highly sensitive to linguistic var…
cs.CV2025
A Fully Transformer Based Multimodal Framework for Explainable Cancer Image Segmentation Using Radiology Reports
Enobong Adahada, Isabel Sassoon, Kate Hone +1
We introduce Med-CTX, a fully transformer based multimodal framework for explainable breast cancer ultrasound segmentation. We integrate clinical radiology reports to boost both pe…
eess.IV2024★ 2 cited
Segmenting Medical Images: From UNet to Res-UNet and nnUNet
Lina Huang, Alina Miron, Kate Hone +1
This study provides a comparative analysis of deep learning models including UNet, Res-UNet, Attention Res-UNet, and nnUNet, and evaluates their performance in brain tumour, polyp,…