494 citations · 723 across the 8 of their papers we have counts for
8 papers
PanopMamba: Vision State Space Modeling for Nuclei Panoptic Segmentation
Ming Kang, Fung Fung Ting, Raphaël C. -W. Phan +2
Nuclei panoptic segmentation supports cancer diagnostics by integrating both semantic and instance segmentation of different cell types to analyze overall tissue structure and indi…
HyTver: A Novel Loss Function for Longitudinal Multiple Sclerosis Lesion Segmentation
Dayan Perera, Ting Fung Fung, Vishnu Monn
Longitudinal Multiple Sclerosis Lesion Segmentation is a particularly challenging problem that involves both input and output imbalance in the data and segmentation. Therefore in 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…
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…
ASF-YOLO: A Novel YOLO Model with Attentional Scale Sequence Fusion for Cell Instance Segmentation
Ming Kang, Chee-Ming Ting, Fung Fung Ting +1
We propose a novel Attentional Scale Sequence Fusion based You Only Look Once (YOLO) framework (ASF-YOLO) which combines spatial and scale features for accurate and fast cell insta…
BGF-YOLO: Enhanced YOLOv8 with Multiscale Attentional Feature Fusion for Brain Tumor Detection
Ming Kang, Chee-Ming Ting, Fung Fung Ting +1
You Only Look Once (YOLO)-based object detectors have shown remarkable accuracy for automated brain tumor detection. In this paper, we develop a novel BGF-YOLO architecture by inco…
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…
CST-YOLO: A Novel Method for Blood Cell Detection Based on Improved YOLOv7 and CNN-Swin Transformer
Ming Kang, Chee-Ming Ting, Fung Fung Ting +1
Blood cell detection is a typical small-scale object detection problem in computer vision. In this paper, we propose a CST-YOLO model for blood cell detection based on YOLOv7 archi…