activity
20192025
most citedA comparison of Monte Carlo dropout and bootstrap aggregation on the performance and uncertainty estimation in radiation therapy dose prediction with deep learning neural networks

3 citations · 5 across the 6 of their papers we have counts for

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Showing 2023Show all

2 papers · 1 filter

cs.CV2023

Exploring UMAP in hybrid models of entropy-based and representativeness sampling for active learning in biomedical segmentation

H. S. Tan, Kuancheng Wang, Rafe Mcbeth

In this work, we study various hybrid models of entropy-based and representativeness sampling techniques in the context of active learning in medical segmentation, in particular ex…

eess.IV2023

Swin UNETR++: Advancing Transformer-Based Dense Dose Prediction Towards Fully Automated Radiation Oncology Treatments

Kuancheng Wang, Hai Siong Tan, Rafe Mcbeth

The field of Radiation Oncology is uniquely positioned to benefit from the use of artificial intelligence to fully automate the creation of radiation treatment plans for cancer the…