most citedExploring Vanilla U-Net for Lesion Segmentation from Whole-body FDG-PET/CT Scans

10 citations · 31 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2023★ 8 cited

SegMatch: A semi-supervised learning method for surgical instrument segmentation

Meng Wei, Charlie Budd, Luis C. Garcia-Peraza-Herrera +3

Surgical instrument segmentation is recognised as a key enabler in providing advanced surgical assistance and improving computer-assisted interventions. In this work, we propose Se…

cs.CV2023★ 2 cited

Pick the Best Pre-trained Model: Towards Transferability Estimation for Medical Image Segmentation

Yuncheng Yang, Meng Wei, Junjun He +3

Transfer learning is a critical technique in training deep neural networks for the challenging medical image segmentation task that requires enormous resources. With the abundance…

cs.CV2023★ 8 cited

Text Promptable Surgical Instrument Segmentation with Vision-Language Models

Zijian Zhou, Oluwatosin Alabi, Meng Wei +2

In this paper, we propose a novel text promptable surgical instrument segmentation approach to overcome challenges associated with diversity and differentiation of surgical instrum…

eess.IV2022★ 10 cited

Exploring Vanilla U-Net for Lesion Segmentation from Whole-body FDG-PET/CT Scans

Jin Ye, Haoyu Wang, Ziyan Huang +8

Tumor lesion segmentation is one of the most important tasks in medical image analysis. In clinical practice, Fluorodeoxyglucose Positron-Emission Tomography~(FDG-PET) is a widely…

cs.CV2022★ 3 cited

Counting with Adaptive Auxiliary Learning

Yanda Meng, Joshua Bridge, Meng Wei +5

This paper proposes an adaptive auxiliary task learning based approach for object counting problems. Unlike existing auxiliary task learning based methods, we develop an attention-…