4 citations · 8 across the 3 of their papers we have counts for
3 papers
eess.IV2023★ 4 cited
RADIFUSION: A multi-radiomics deep learning based breast cancer risk prediction model using sequential mammographic images with image attention and bilateral asymmetry refinement
Hong Hui Yeoh, Andrea Liew, Raphaël Phan +5
Breast cancer is a significant public health concern and early detection is critical for triaging high risk patients. Sequential screening mammograms can provide important spatiote…
eess.IV2021
CASPIANET++: A Multidimensional Channel-Spatial Asymmetric Attention Network with Noisy Student Curriculum Learning Paradigm for Brain Tumor Segmentation
Andrea Liew, Chun Cheng Lee, Boon Leong Lan +1
Convolutional neural networks (CNNs) have been used quite successfully for semantic segmentation of brain tumors. However, current CNNs and attention mechanisms are stochastic in n…
eess.IV2020★ 4 cited
A new semi-supervised self-training method for lung cancer prediction
Kelvin Shak, Mundher Al-Shabi, Andrea Liew +4
Background and Objective: Early detection of lung cancer is crucial as it has high mortality rate with patients commonly present with the disease at stage 3 and above. There are on…