95 citations · 302 across the 8 of their papers we have counts for
8 papers
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…
Lung Nodule Classification using Deep Local-Global Networks
Mundher Al-Shabi, Boon Leong Lan, Wai Yee Chan +2
Purpose: Lung nodules have very diverse shapes and sizes, which makes classifying them as benign/malignant a challenging problem. In this paper, we propose a novel method to predic…
Gated-Dilated Networks for Lung Nodule Classification in CT scans
Mundher Al-Shabi, Hwee Kuan Lee, Maxine Tan
Different types of Convolutional Neural Networks (CNNs) have been applied to detect cancerous lung nodules from computed tomography (CT) scans. However, the size of a nodule is ver…
Smart Content Recognition from Images Using a Mixture of Convolutional Neural Networks
Tee Connie, Mundher Al-Shabi, Michael Goh
With rapid development of the Internet, web contents become huge. Most of the websites are publicly available, and anyone can access the contents from anywhere such as workplace, h…
Facial Expression Recognition Using a Hybrid CNN-SIFT Aggregator
Mundher Al-Shabi, Wooi Ping Cheah, Tee Connie
Deriving an effective facial expression recognition component is important for a successful human-computer interaction system. Nonetheless, recognizing facial expression remains a…