Publications (34)
CAFCT-Net: A CNN-Transformer Hybrid Network with Contextual and Attentional Feature Fusion for Liver Tumor Segmentation
Ming Kang, Chee-Ming Ting, Fung Fung Ting +1
Medical image semantic segmentation techniques can help identify tumors automatically from computed tomography (CT) scans. In this paper, we propose a Contextual and Attentional fe…
Graph-Regularized Manifold-Aware Conditional Wasserstein GAN for Brain Functional Connectivity Generation
Yee-Fan Tan, Chee-Ming Ting, Fuad Noman +2
Common measures of brain functional connectivity (FC) including covariance and correlation matrices are semi-positive definite (SPD) matrices residing on a cone-shape Riemannian ma…
RCS-YOLO: A Fast and High-Accuracy Object Detector for Brain Tumor Detection
Ming Kang, Chee-Ming Ting, Fung Fung Ting +1
With an excellent balance between speed and accuracy, cutting-edge YOLO frameworks have become one of the most efficient algorithms for object detection. However, the performance o…
PK-YOLO: Pretrained Knowledge Guided YOLO for Brain Tumor Detection in Multiplanar MRI Slices
Ming Kang, Fung Fung Ting, Raphaël C. -W. Phan +1
Brain tumor detection in multiplane Magnetic Resonance Imaging (MRI) slices is a challenging task due to the various appearances and relationships in the structure of the multiplan…
BICNet: A Bayesian Approach for Estimating Task Effects on Intrinsic Connectivity Networks in fMRI Data
Meini Tang, Chee-Ming Ting, Hernando Ombao
Intrinsic connectivity networks (ICNs) are specific dynamic functional brain networks that are consistently found under various conditions including rest and task. Studies have sho…
Graph Autoencoders for Embedding Learning in Brain Networks and Major Depressive Disorder Identification
Fuad Noman, Chee-Ming Ting, Hakmook Kang +4
Brain functional connectivity (FC) reveals biomarkers for identification of various neuropsychiatric disorders. Recent application of deep neural networks (DNNs) to connectome-base…