95 citations · 302 across the 8 of their papers we have counts for
4 papers · 1 filter
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…
3D Axial-Attention for Lung Nodule Classification
Mundher Al-Shabi, Kelvin Shak, Maxine Tan
Purpose: In recent years, Non-Local based methods have been successfully applied to lung nodule classification. However, these methods offer 2D attention or limited 3D attention to…
ProCAN: Progressive Growing Channel Attentive Non-Local Network for Lung Nodule Classification
Mundher Al-Shabi, Kelvin Shak, Maxine Tan
Lung cancer classification in screening computed tomography (CT) scans is one of the most crucial tasks for early detection of this disease. Many lives can be saved if we are able…
Cribriform pattern detection in prostate histopathological images using deep learning models
Malay Singh, Emarene Mationg Kalaw, Wang Jie +7
Architecture, size, and shape of glands are most important patterns used by pathologists for assessment of cancer malignancy in prostate histopathological tissue slides. Varying st…